diff --git a/docs/source/user_guide/notebooks/Audio-get_acoustic_features.ipynb b/docs/source/user_guide/notebooks/Audio-get_acoustic_features.ipynb
index bc79422..aee6073 100644
--- a/docs/source/user_guide/notebooks/Audio-get_acoustic_features.ipynb
+++ b/docs/source/user_guide/notebooks/Audio-get_acoustic_features.ipynb
@@ -60,7 +60,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-08 19:49:08</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">OCEANAI - персональные качества личности человека:</span>**<br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Авторы:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Карпов Алексей [<u>karpov@iias.spb.su</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Сопровождающие:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Версия: <u>1.0.0a40</u></span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Лицензия: <u>BSD License</u></span></p>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 16:38:10</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">OCEANAI - персональные качества личности человека:</span>**<br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Авторы:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Карпов Алексей [<u>karpov@iias.spb.su</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Сопровождающие:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Версия: <u>1.0.0a40</u></span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Лицензия: <u>BSD License</u></span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -167,7 +167,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.11"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/user_guide/notebooks/Pipeline_practical_task_1.ipynb b/docs/source/user_guide/notebooks/Pipeline_practical_task_1.ipynb
index 2a87132..7a35e9e 100644
--- a/docs/source/user_guide/notebooks/Pipeline_practical_task_1.ipynb
+++ b/docs/source/user_guide/notebooks/Pipeline_practical_task_1.ipynb
@@ -60,7 +60,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:42:02</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:13:14</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -72,7 +72,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:42:05</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_FI\\test\\_plk5k7PBEg.003.mp4 ...</span></p>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:13:15</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_FI\\test\\_plk5k7PBEg.003.mp4 ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -123,92 +123,92 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581159</td>\n",
-       "      <td>0.628822</td>\n",
-       "      <td>0.466609</td>\n",
-       "      <td>0.622129</td>\n",
-       "      <td>0.553832</td>\n",
+       "      <td>0.618917</td>\n",
+       "      <td>0.660694</td>\n",
+       "      <td>0.477656</td>\n",
+       "      <td>0.654437</td>\n",
+       "      <td>0.601256</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.463991</td>\n",
-       "      <td>0.418851</td>\n",
-       "      <td>0.41301</td>\n",
-       "      <td>0.493329</td>\n",
-       "      <td>0.423093</td>\n",
+       "      <td>0.461732</td>\n",
+       "      <td>0.413451</td>\n",
+       "      <td>0.415706</td>\n",
+       "      <td>0.498301</td>\n",
+       "      <td>0.431224</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
-       "      <td>0.454281</td>\n",
-       "      <td>0.415049</td>\n",
-       "      <td>0.39189</td>\n",
-       "      <td>0.485114</td>\n",
-       "      <td>0.420741</td>\n",
+       "      <td>0.468002</td>\n",
+       "      <td>0.448618</td>\n",
+       "      <td>0.371742</td>\n",
+       "      <td>0.509602</td>\n",
+       "      <td>0.453739</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588461</td>\n",
-       "      <td>0.643233</td>\n",
-       "      <td>0.530789</td>\n",
-       "      <td>0.603038</td>\n",
-       "      <td>0.593398</td>\n",
+       "      <td>0.585348</td>\n",
+       "      <td>0.616446</td>\n",
+       "      <td>0.49443</td>\n",
+       "      <td>0.605614</td>\n",
+       "      <td>0.587017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633433</td>\n",
-       "      <td>0.533295</td>\n",
-       "      <td>0.523742</td>\n",
-       "      <td>0.608591</td>\n",
-       "      <td>0.588456</td>\n",
+       "      <td>0.680991</td>\n",
+       "      <td>0.56602</td>\n",
+       "      <td>0.553915</td>\n",
+       "      <td>0.646545</td>\n",
+       "      <td>0.64246</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.636944</td>\n",
-       "      <td>0.542386</td>\n",
-       "      <td>0.558461</td>\n",
-       "      <td>0.570975</td>\n",
-       "      <td>0.558983</td>\n",
+       "      <td>0.66342</td>\n",
+       "      <td>0.551018</td>\n",
+       "      <td>0.557912</td>\n",
+       "      <td>0.585238</td>\n",
+       "      <td>0.587174</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
-       "      <td>0.531518</td>\n",
-       "      <td>0.376987</td>\n",
-       "      <td>0.393309</td>\n",
-       "      <td>0.4904</td>\n",
-       "      <td>0.447881</td>\n",
+       "      <td>0.590237</td>\n",
+       "      <td>0.399273</td>\n",
+       "      <td>0.409554</td>\n",
+       "      <td>0.531861</td>\n",
+       "      <td>0.507134</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610342</td>\n",
-       "      <td>0.541418</td>\n",
-       "      <td>0.563163</td>\n",
-       "      <td>0.595013</td>\n",
-       "      <td>0.569461</td>\n",
+       "      <td>0.60577</td>\n",
+       "      <td>0.523617</td>\n",
+       "      <td>0.531137</td>\n",
+       "      <td>0.594406</td>\n",
+       "      <td>0.57984</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.495809</td>\n",
-       "      <td>0.458526</td>\n",
-       "      <td>0.414436</td>\n",
-       "      <td>0.469152</td>\n",
-       "      <td>0.435461</td>\n",
+       "      <td>0.511002</td>\n",
+       "      <td>0.464702</td>\n",
+       "      <td>0.390882</td>\n",
+       "      <td>0.443663</td>\n",
+       "      <td>0.438811</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.60707</td>\n",
-       "      <td>0.591893</td>\n",
-       "      <td>0.520662</td>\n",
-       "      <td>0.603938</td>\n",
-       "      <td>0.565726</td>\n",
+       "      <td>0.647606</td>\n",
+       "      <td>0.610466</td>\n",
+       "      <td>0.524718</td>\n",
+       "      <td>0.61428</td>\n",
+       "      <td>0.606428</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -217,29 +217,29 @@
       "text/plain": [
        "                          Path  Openness Conscientiousness Extraversion  \\\n",
        "Person ID                                                                 \n",
-       "1          2d6btbaNdfo.000.mp4  0.581159          0.628822     0.466609   \n",
-       "2          300gK3CnzW0.001.mp4  0.463991          0.418851      0.41301   \n",
-       "3          300gK3CnzW0.003.mp4  0.454281          0.415049      0.39189   \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588461          0.643233     0.530789   \n",
-       "5          be0DQawtVkE.002.mp4  0.633433          0.533295     0.523742   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.636944          0.542386     0.558461   \n",
-       "7          g24JGYuT74A.004.mp4  0.531518          0.376987     0.393309   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610342          0.541418     0.563163   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.495809          0.458526     0.414436   \n",
-       "10         _plk5k7PBEg.003.mp4   0.60707          0.591893     0.520662   \n",
+       "1          2d6btbaNdfo.000.mp4  0.618917          0.660694     0.477656   \n",
+       "2          300gK3CnzW0.001.mp4  0.461732          0.413451     0.415706   \n",
+       "3          300gK3CnzW0.003.mp4  0.468002          0.448618     0.371742   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585348          0.616446      0.49443   \n",
+       "5          be0DQawtVkE.002.mp4  0.680991           0.56602     0.553915   \n",
+       "6          cLaZxEf1nE4.004.mp4   0.66342          0.551018     0.557912   \n",
+       "7          g24JGYuT74A.004.mp4  0.590237          0.399273     0.409554   \n",
+       "8          JZNMxa3OKHY.000.mp4   0.60577          0.523617     0.531137   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511002          0.464702     0.390882   \n",
+       "10         _plk5k7PBEg.003.mp4  0.647606          0.610466     0.524718   \n",
        "\n",
        "          Agreeableness Non-Neuroticism  \n",
        "Person ID                                \n",
-       "1              0.622129        0.553832  \n",
-       "2              0.493329        0.423093  \n",
-       "3              0.485114        0.420741  \n",
-       "4              0.603038        0.593398  \n",
-       "5              0.608591        0.588456  \n",
-       "6              0.570975        0.558983  \n",
-       "7                0.4904        0.447881  \n",
-       "8              0.595013        0.569461  \n",
-       "9              0.469152        0.435461  \n",
-       "10             0.603938        0.565726  "
+       "1              0.654437        0.601256  \n",
+       "2              0.498301        0.431224  \n",
+       "3              0.509602        0.453739  \n",
+       "4              0.605614        0.587017  \n",
+       "5              0.646545         0.64246  \n",
+       "6              0.585238        0.587174  \n",
+       "7              0.531861        0.507134  \n",
+       "8              0.594406         0.57984  \n",
+       "9              0.443663        0.438811  \n",
+       "10              0.61428        0.606428  "
       ]
      },
      "metadata": {},
@@ -248,7 +248,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:42:05</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:13:15</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -298,21 +298,21 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MAE</th>\n",
-       "      <td>0.0589</td>\n",
-       "      <td>0.0612</td>\n",
-       "      <td>0.0864</td>\n",
-       "      <td>0.0697</td>\n",
-       "      <td>0.0582</td>\n",
-       "      <td>0.0669</td>\n",
+       "      <td>0.0735</td>\n",
+       "      <td>0.0631</td>\n",
+       "      <td>0.0914</td>\n",
+       "      <td>0.0706</td>\n",
+       "      <td>0.0691</td>\n",
+       "      <td>0.0735</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.9411</td>\n",
-       "      <td>0.9388</td>\n",
-       "      <td>0.9136</td>\n",
-       "      <td>0.9303</td>\n",
-       "      <td>0.9418</td>\n",
-       "      <td>0.9331</td>\n",
+       "      <td>0.9265</td>\n",
+       "      <td>0.9369</td>\n",
+       "      <td>0.9086</td>\n",
+       "      <td>0.9294</td>\n",
+       "      <td>0.9309</td>\n",
+       "      <td>0.9265</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -321,13 +321,13 @@
       "text/plain": [
        "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
        "Metrics                                                              \n",
-       "MAE         0.0589             0.0612        0.0864         0.0697   \n",
-       "Accuracy    0.9411             0.9388        0.9136         0.9303   \n",
+       "MAE         0.0735             0.0631        0.0914         0.0706   \n",
+       "Accuracy    0.9265             0.9369        0.9086         0.9294   \n",
        "\n",
        "          Non-Neuroticism    Mean  \n",
        "Metrics                            \n",
-       "MAE                0.0582  0.0669  \n",
-       "Accuracy           0.9418  0.9331  "
+       "MAE                0.0691  0.0735  \n",
+       "Accuracy           0.9309  0.9265  "
       ]
      },
      "metadata": {},
@@ -336,7 +336,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:42:05</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0669</span>, средняя точность: <span style=\"color:#1776D2\">0.9331</span> ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:13:15</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0735</span>, средняя точность: <span style=\"color:#1776D2\">0.9265</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -360,7 +360,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 64.481 сек. ---**</span>"
+       "<span style=\"color:#666\">**--- Время выполнения: 34.472 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -402,11 +402,11 @@
     "res_load_model_nn = _b5.load_audio_model_nn()\n",
     "\n",
     "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование видеомоделей\n",
     "res_load_model_hc = _b5.load_video_model_hc(lang='en')\n",
@@ -414,37 +414,36 @@
     "res_load_model_nn = _b5.load_video_model_nn()\n",
     "\n",
     "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
     "res_load_text_features = _b5.load_text_features()\n",
     "\n",
     "# Формирование текстовых моделей \n",
-    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
-    "res_setup_translation_model = _b5.setup_bert_encoder()\n",
+    "res_setup_bert_model = _b5.setup_bert_encoder(force_reload = False)\n",
     "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
     "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
     "\n",
     "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование модели для мультимодального объединения информации\n",
     "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
     "\n",
     "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
     "\n",
     "PATH_TO_DIR = './video_FI/'\n",
     "PATH_SAVE_VIDEO = './video_FI/test/'\n",
@@ -475,7 +474,7 @@
     "_b5.ext_ = ['.mp4'] # Расширения искомых файлов\n",
     "\n",
     "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_[corpus]['sberdisk']\n",
+    "url_accuracy = _b5.true_traits_[corpus]['googledisk']\n",
     "\n",
     "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = 'en')"
    ]
@@ -685,102 +684,102 @@
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>60.246</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>64.644</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>62.472</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2d6btbaNdfo.000.mp4</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>62.080</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>59.725</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>61.812</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>59.672</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>59.380</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>58.876</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
-       "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
-       "      <td>58.921</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>58.463</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>58.412</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
        "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>48.271</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>53.134</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
-       "      <td>47.310</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
-       "      <td>45.294</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>47.712</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
        "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
-       "      <td>44.487</td>\n",
+       "      <td>46.438</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>45.310</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -789,29 +788,29 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                           \n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559   \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593   \n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569   \n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554   \n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435   \n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423   \n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431   \n",
        "\n",
        "           Candidate score  \n",
        "Person ID                   \n",
-       "5                   60.246  \n",
-       "6                   59.725  \n",
-       "4                   59.672  \n",
-       "10                  59.380  \n",
-       "8                   58.921  \n",
-       "1                   58.463  \n",
-       "7                   48.271  \n",
-       "9                   47.310  \n",
-       "2                   45.294  \n",
-       "3                   44.487  "
+       "5                   64.644  \n",
+       "10                  62.472  \n",
+       "1                   62.080  \n",
+       "6                   61.812  \n",
+       "4                   58.876  \n",
+       "8                   58.412  \n",
+       "7                   53.134  \n",
+       "9                   47.712  \n",
+       "3                   46.438  \n",
+       "2                   45.310  "
       ]
      },
      "execution_count": 4,
@@ -897,104 +896,104 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>60.360</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>59.158</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>62.212</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
+       "      <th>5</th>\n",
+       "      <td>be0DQawtVkE.002.mp4</td>\n",
+       "      <td>0.681</td>\n",
        "      <td>0.566</td>\n",
-       "      <td>58.579</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>60.943</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
        "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
-       "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
-       "      <td>57.250</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>60.412</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>57.223</td>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>58.876</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>56.839</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
-       "      <td>45.954</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>58.099</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
-       "      <td>44.730</td>\n",
+       "      <th>8</th>\n",
+       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>56.112</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
        "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>44.018</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>47.463</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
        "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
-       "      <td>43.876</td>\n",
+       "      <td>45.855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>45.297</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>44.737</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1003,29 +1002,29 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                           \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593   \n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554   \n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569   \n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435   \n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423   \n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448   \n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431   \n",
        "\n",
        "           Candidate score  \n",
        "Person ID                   \n",
-       "4                   60.360  \n",
-       "1                   59.158  \n",
-       "10                  58.579  \n",
-       "8                   57.250  \n",
-       "5                   57.223  \n",
-       "6                   56.839  \n",
-       "9                   45.954  \n",
-       "2                   44.730  \n",
-       "7                   44.018  \n",
-       "3                   43.876  "
+       "1                   62.212  \n",
+       "5                   60.943  \n",
+       "10                  60.412  \n",
+       "4                   58.876  \n",
+       "6                   58.099  \n",
+       "8                   56.112  \n",
+       "7                   47.463  \n",
+       "3                   45.855  \n",
+       "9                   45.297  \n",
+       "2                   44.737  "
       ]
      },
      "execution_count": 5,
@@ -1324,133 +1323,133 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.380</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.561</td>\n",
-       "      <td>0.454</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>0.376</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.539</td>\n",
-       "      <td>0.465</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.367</td>\n",
-       "      <td>0.398</td>\n",
-       "      <td>0.543</td>\n",
-       "      <td>0.439</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>0.397</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.571</td>\n",
+       "      <td>0.491</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.360</td>\n",
-       "      <td>0.389</td>\n",
-       "      <td>0.534</td>\n",
-       "      <td>0.431</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.571</td>\n",
+       "      <td>0.461</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
        "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.379</td>\n",
+       "      <td>0.414</td>\n",
        "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
-       "      <td>0.357</td>\n",
-       "      <td>0.383</td>\n",
-       "      <td>0.528</td>\n",
-       "      <td>0.425</td>\n",
+       "      <td>0.456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.375</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.538</td>\n",
+       "      <td>0.464</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.350</td>\n",
-       "      <td>0.379</td>\n",
-       "      <td>0.523</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.359</td>\n",
+       "      <td>0.390</td>\n",
+       "      <td>0.537</td>\n",
+       "      <td>0.433</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>0.353</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>0.522</td>\n",
        "      <td>0.421</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
-       "      <td>0.096</td>\n",
-       "      <td>0.074</td>\n",
-       "      <td>0.075</td>\n",
-       "      <td>0.107</td>\n",
+       "      <th>7</th>\n",
+       "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
+       "      <td>0.532</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>0.240</td>\n",
+       "      <td>0.249</td>\n",
+       "      <td>0.331</td>\n",
+       "      <td>0.298</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.454</td>\n",
+       "      <td>0.198</td>\n",
+       "      <td>0.154</td>\n",
+       "      <td>0.198</td>\n",
+       "      <td>0.202</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
+       "      <td>0.462</td>\n",
        "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
        "      <td>0.093</td>\n",
        "      <td>0.072</td>\n",
        "      <td>0.073</td>\n",
-       "      <td>0.104</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>300gK3CnzW0.003.mp4</td>\n",
-       "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
-       "      <td>0.091</td>\n",
-       "      <td>0.071</td>\n",
-       "      <td>0.072</td>\n",
-       "      <td>0.102</td>\n",
+       "      <td>0.105</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>g24JGYuT74A.004.mp4</td>\n",
-       "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>0.082</td>\n",
+       "      <th>9</th>\n",
+       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>0.083</td>\n",
        "      <td>0.094</td>\n",
-       "      <td>0.119</td>\n",
+       "      <td>0.118</td>\n",
        "      <td>0.136</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -1460,29 +1459,29 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  Analytical  \\\n",
        "Person ID                                                                       \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593       0.380   \n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554       0.376   \n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566       0.367   \n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588       0.360   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569       0.357   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559       0.350   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435       0.096   \n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423       0.093   \n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421       0.091   \n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448       0.082   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601       0.397   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642       0.384   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606       0.379   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587       0.375   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587       0.359   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580       0.353   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507       0.240   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454       0.198   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431       0.093   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439       0.083   \n",
        "\n",
        "           Interactive  Routine  Non-Routine  \n",
        "Person ID                                     \n",
-       "4                0.415    0.561        0.454  \n",
-       "1                0.427    0.539        0.465  \n",
-       "10               0.398    0.543        0.439  \n",
-       "5                0.389    0.534        0.431  \n",
-       "8                0.383    0.528        0.425  \n",
-       "6                0.379    0.523        0.421  \n",
-       "9                0.074    0.075        0.107  \n",
-       "2                0.072    0.073        0.104  \n",
-       "3                0.071    0.072        0.102  \n",
-       "7                0.094    0.119        0.136  "
+       "1                0.452    0.571        0.491  \n",
+       "5                0.416    0.571        0.461  \n",
+       "10               0.414    0.563        0.456  \n",
+       "4                0.426    0.538        0.464  \n",
+       "6                0.390    0.537        0.433  \n",
+       "8                0.380    0.522        0.421  \n",
+       "7                0.249    0.331        0.298  \n",
+       "3                0.154    0.198        0.202  \n",
+       "2                0.072    0.073        0.105  \n",
+       "9                0.094    0.118        0.136  "
       ]
      },
      "execution_count": 7,
@@ -1508,22 +1507,551 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2297292e-1e4b-44e0-9c85-ab0fba999892",
+   "id": "a4283405",
    "metadata": {},
    "source": [
-    "### `MuPTA` (ru)"
+    "<hr>\n",
+    "\n",
+    "Для ранжирования кандидатов по одному из шестнадцати типов личности MBTI необходимо задать матрицу корреляции между персональными качествами личности человека и четырьмя диспозициями MBTI, установить порог полярности качеств и указать целевой тип личности MBTI.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции, представленных в статье [1]. Описание типов личности MBTI и соотвествующие им успешные профессии представлены в статье [2].\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "2) Tieger P.D., Barron B., Tieger K. Do what you are: Discover the perfect career for you through the secrets of personality type // Hachette UK. - 2024.\n",
+    "\n",
+    "##### Типы личности MBTI основаны на четырех измерениях личности:\n",
+    "\n",
+    "<div style=\"text-align: center;\">\n",
+    "  <table style=\"width:100%; margin: 0 auto; font-size: 0.6em;\">\n",
+    "    <tr>\n",
+    "      <th>Описание измерения</th>\n",
+    "      <th>Измерение</th>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Как мы взаимодействуем с миром и куда направляем свою энергию</td>\n",
+    "      <td>(E) Экстраверсия - Интроверсия (I)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Вид информации, которую мы естественным образом замечаем</td>\n",
+    "      <td>(S) Сенсорика - Интуиция (N)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Как мы принимаем решения</td>\n",
+    "      <td>(T) Логика - Чувства (F)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Предпочитаем ли мы жить более структурированно (принимая решения) или более спонтанно (принимая информацию)</td>\n",
+    "      <td>(J) Оценка - Восприятие (P)</td>\n",
+    "    </tr>\n",
+    "  </table>\n",
+    "</div>\n",
+    "\n",
+    "##### Типы личности MBTI и соотвествующие им успешные профессии:\n",
+    "\n",
+    "<div style=\"text-align: center;\">\n",
+    "  <table style=\"width: 100%; margin: 0 auto; font-size: 0.6em;\">\n",
+    "    <tr>\n",
+    "      <th>Тип личности</th>\n",
+    "      <th>Описание</th>\n",
+    "      <th>Успешные профессии</th>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISTJ</td>\n",
+    "      <td>Этот человек отличается ответственностью, строгостью и педантичностью. Он опирается на объективные факты и склонен к аналитическому мышлению. Приступает к задаче только тогда, когда уверен в своих возможностях и успехе</td>\n",
+    "      <td>Инспектор: бухгалтер, аудитор, бюджетный аналитик, финансовый менеджер, разработчик, системный аналитик, библиотекарь и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISFJ</td>\n",
+    "      <td>Этот человек склонен к самоанализу и анализу окружающих, легко распознает фальшь и предпочитает сохранять психологическую дистанцию. Он исполнителен, внимателен и готов помогать другим. Его силы и энергия исходят из внутренних ресурсов, и он всегда полагается на собственный опыт</td>\n",
+    "      <td>Защитник: медсестра, врач, ветеринар или ветеринарный ассистент, социальный работник, сельскохозяйственный или пищевой ученый, секретарь, водитель и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INFJ</td>\n",
+    "      <td>О таких людях говорят: «ему можно доверять». Он отличается высокой чувствительностью, уделяет большое внимание межличностным отношениям, умеет давать ценные советы и помогает раскрывать потенциал других. Развитая интуиция не только генерирует множество идей, но и способствует самоорганизации</td>\n",
+    "      <td>Советник: психолог, специалист по управлению персоналом, офис-менеджер, специалист по обучению, графический дизайнер и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INTJ</td>\n",
+    "      <td>Этот человек умеет выделять главное, говорит четко и по существу, придерживается практического подхода. Он стремится постоянно улучшать свою работу и всегда ищет способы сделать задачу еще лучше. Пустые разговоры ему не по душе, поэтому он избегает больших шумных компаний и с трудом заводит новые знакомства</td>\n",
+    "      <td>Мастермайнд: аниматор, архитектор, копирайтер, фотограф, тележурналист, видеомонтажер, специалист по бизнес-развитию, исполнительный директор, профессор и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISTP</td>\n",
+    "      <td>Этот человек воспринимает мир через ощущения. По природе эмпат, но чаще сосредоточен на себе. Его умение объективно принимать решения и анализировать ситуацию указывает на технический склад ума. Он всегда соблюдает дедлайны, хотя иногда может поступить неожиданно</td>\n",
+    "      <td>Создатель: инженер, техник, строитель, инспектор, судебный эксперт, программист, разработчик ПО и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISFP</td>\n",
+    "      <td>Этот человек умеет находить радость в однообразии и рутинных делах. Прекрасно ладит с людьми, избегая конфликтов. Ему важно чувствовать свою значимость и оказывать помощь. Такой человек не стремится руководить или менять других, уважает их личные границы и ожидает того же в ответ. По натуре он приземленный практик, на которого всегда можно положиться</td>\n",
+    "      <td>Композитор: помощник по маркетингу, танцор, шеф-повар, офис-администратор, художник, дизайнер интерьеров, секретарь, медсестра и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INFP</td>\n",
+    "      <td>Этот человек - чувствительный лирик, прекрасно разбирающийся в людях и легко вызывающий у них симпатию. Он обладает отличным чувством юмора и уделяет большое внимание своему внешнему виду. Стремится к самопознанию, гармонии с собой и старается быть полезным окружающим</td>\n",
+    "      <td>Целитель: писатель, дизайнер мультимедиа, менеджер по работе с клиентами, учитель для детей с особыми потребностями, тренер, редактор, модельер и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INTP</td>\n",
+    "      <td>Этот человек - эрудит с философским складом ума. Он тщательно анализирует свои решения, стремясь к объективности и беспристрастности. Бурные проявления эмоций ему не свойственны. Однако большое количество данных и их изменчивость могут вызывать у него внутреннее напряжение</td>\n",
+    "      <td>Архитектор: технический писатель, веб-разработчик, аналитик информационной безопасности, исследователь, ученый, юрист и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESTP</td>\n",
+    "      <td>Этот человек всегда добивается успеха, невзирая на препятствия, которые лишь усиливают его целеустремленность. Он стремится к лидерским позициям и плохо переносит роль подчиненного. Обычно разрабатывает четкий план действий и неуклонно ему следует</td>\n",
+    "      <td>Промоутер: специалист по работе с клиентами, актер, личный тренер, бренд-амбассадор, менеджер, предприниматель, креативный директор, полицейский, маркетолог, производитель и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESFP</td>\n",
+    "      <td>Этот человек легко выявляет слабые стороны людей, что позволяет ему эффективно манипулировать и управлять. В общении он чаще всего руководствуется собственными интересами и предпочитает жить в настоящем. Часто не завершает начатое, стремясь к быстрым результатам. Однако при этом стремится поддерживать гармоничные отношения с окружающими</td>\n",
+    "      <td>Исполнитель: бортпроводник, артист, учитель, менеджер по связям с общественностью, торговый представитель, организатор мероприятий и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ENFP</td>\n",
+    "      <td>Этот человек - творческая личность и фантазер, обладающий качествами, которые помогают ему успешно взаимодействовать с другими, быть открытым и общительным. Он активно участвует в различных мероприятиях, легко решает возникающие вопросы и демонстрирует гибкость</td>\n",
+    "      <td>Чемпион: медицинский работник, продюсер, продавец-консультант, специалист по обслуживанию клиентов, сценарист, ведущий на ТВ/радио и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ENTP</td>\n",
+    "      <td>Этот человек - изобретательный, инициативный и гибкий. Он генератор идей и первопроходец, который не выносит рутины. Постоянное движение и интуитивное принятие решений всегда сопровождают его в работе</td>\n",
+    "      <td>Новатор: инженер, маркетолог, менеджер по социальным сетям, аналитик управления, руководитель цифрового маркетинга, бизнес-консультант, разработчик игр, менеджер по продажам и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESTJ</td>\n",
+    "      <td>Это трудолюбивый человек, который воспринимает мир таким, какой он есть. Он склонен тщательно планировать и доводить дела до конца. Заботится о своем ближайшем окружении, проявляет добродушие, но иногда может быть вспыльчивым, резким и упрямым</td>\n",
+    "      <td>Супервайзер: управляющий директор, менеджер отеля, финансовый сотрудник, судья, агент по недвижимости, генеральный директор, шеф-повар, менеджер по бизнес-развитию, телемаркетолог и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESFJ</td>\n",
+    "      <td>Этот человек умеет оказывать влияние на людей, проявляет заботу и готов жертвовать собой ради других. Он легко устанавливает контакт с любым человеком и способен направить ситуацию в нужное ему русло</td>\n",
+    "      <td>Поставщик: специалист по технической поддержке, менеджер по работе с клиентами, профессор колледжа, медицинский исследователь, бухгалтер, фотожурналист и т. д.</td>\n",
+    "    </tr>\n",
+    "    <td>ENFJ</td>\n",
+    "      <td>Этот человек отличается эмоциональностью и эмпатией. Его мимика выразительна, а речь — красноречива. Благодаря своей самоорганизованности, он успешно воплощает свои фантазии и идеи в жизнь. Он интуитивно понимает, какое решение следует принять в каждой конкретной ситуации</td>\n",
+    "      <td>Учитель: менеджер по связям с общественностью, менеджер по продажам, директор по управлению персоналом, арт-директор, консультант и т. д.</td>\n",
+    "    </tr>\n",
+    "    <td>ENTJ</td>\n",
+    "      <td>Этот человек легко увлекается, готов рисковать и полагается на интуицию. Без страха внедряет новые технологии и способен глубоко анализировать как себя, так и окружающий мир. Жизнь для него - это борьба, в которой он чувствует себя уверенно. Открыт для новых возможностей, но при этом нуждается в контроле</td>\n",
+    "      <td>Командир: руководитель строительства, администратор службы здравоохранения, финансовый бухгалтер, аудитор, юрист, директор школы, химический инженер, менеджер баз данных и т. д.</td>\n",
+    "    </tr>\n",
+    "  </table>\n",
+    "</div>\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции и ранжировать кандидатов по другим типам личности."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d0a65bd1",
+   "metadata": {},
+   "source": [
+    "#### Ранжирование кандидатов по одному из шестнадцати типов личности по версии MBTI"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "3887d07c-eef2-4980-8d82-cabf6568aa7d",
+   "execution_count": 8,
+   "id": "18dc8c49",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.14</td>\n",
+       "      <td>-0.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>-0.04</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>-0.35</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Trait    EI    SN    TF    JP\n",
+       "ID                                           \n",
+       "1            Openness  0.09 -0.03 -0.14 -0.16\n",
+       "2   Conscientiousness  0.04 -0.04  0.20  0.14\n",
+       "3        Extraversion  0.20 -0.03  0.01 -0.07\n",
+       "4       Agreeableness  0.02  0.05 -0.35  0.03\n",
+       "5     Non-Neuroticism  0.08  0.00  0.16  0.00"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "\n",
+    "df_correlation_coefficients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fff740f8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>MBTI_Score</th>\n",
+       "      <th>Match</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>be0DQawtVkE.002.mp4</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>0.259041</td>\n",
+       "      <td>-0.027361</td>\n",
+       "      <td>-0.100093</td>\n",
+       "      <td>-0.049093</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.289871</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>cLaZxEf1nE4.004.mp4</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
+       "      <td>0.558</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.252010</td>\n",
+       "      <td>-0.029419</td>\n",
+       "      <td>-0.087981</td>\n",
+       "      <td>-0.050501</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.277057</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.248447</td>\n",
+       "      <td>-0.028874</td>\n",
+       "      <td>-0.081294</td>\n",
+       "      <td>-0.036454</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.268961</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>0.239967</td>\n",
+       "      <td>-0.025332</td>\n",
+       "      <td>-0.090041</td>\n",
+       "      <td>-0.042964</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.266504</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.454</td>\n",
+       "      <td>-0.160520</td>\n",
+       "      <td>0.068617</td>\n",
+       "      <td>-0.278880</td>\n",
+       "      <td>0.053384</td>\n",
+       "      <td>ISFJ</td>\n",
+       "      <td>0.166132</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2d6btbaNdfo.000.mp4</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>0.047788</td>\n",
+       "      <td>0.002056</td>\n",
+       "      <td>-0.092138</td>\n",
+       "      <td>0.046539</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>0.139850</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
+       "      <td>0.532</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>0.006447</td>\n",
+       "      <td>0.037143</td>\n",
+       "      <td>-0.271593</td>\n",
+       "      <td>-0.105712</td>\n",
+       "      <td>ESFP</td>\n",
+       "      <td>0.139020</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.037527</td>\n",
+       "      <td>0.002895</td>\n",
+       "      <td>-0.081646</td>\n",
+       "      <td>0.045425</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>0.123449</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>-0.094752</td>\n",
+       "      <td>-0.007199</td>\n",
+       "      <td>-0.083317</td>\n",
+       "      <td>-0.132767</td>\n",
+       "      <td>INFP</td>\n",
+       "      <td>0.045258</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>-0.185699</td>\n",
+       "      <td>0.017946</td>\n",
+       "      <td>0.083205</td>\n",
+       "      <td>0.030144</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>0.007536</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Path    OPE    CON    EXT    AGR   NNEU        EI  \\\n",
+       "Person ID                                                                     \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642  0.259041   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587  0.252010   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606  0.248447   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580  0.239967   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454 -0.160520   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601  0.047788   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507  0.006447   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587  0.037527   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439 -0.094752   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431 -0.185699   \n",
+       "\n",
+       "                 SN        TF        JP  MBTI  MBTI_Score  Match  \n",
+       "Person ID                                                         \n",
+       "5         -0.027361 -0.100093 -0.049093  ENFP    0.289871   75.0  \n",
+       "6         -0.029419 -0.087981 -0.050501  ENFP    0.277057   75.0  \n",
+       "10        -0.028874 -0.081294 -0.036454  ENFP    0.268961   75.0  \n",
+       "8         -0.025332 -0.090041 -0.042964  ENFP    0.266504   75.0  \n",
+       "3          0.068617 -0.278880  0.053384  ISFJ    0.166132   50.0  \n",
+       "1          0.002056 -0.092138  0.046539  ESFJ    0.139850   75.0  \n",
+       "7          0.037143 -0.271593 -0.105712  ESFP    0.139020   50.0  \n",
+       "4          0.002895 -0.081646  0.045425  ESFJ    0.123449   75.0  \n",
+       "9         -0.007199 -0.083317 -0.132767  INFP    0.045258   50.0  \n",
+       "2          0.017946  0.083205  0.030144  ISTJ    0.007536   25.0  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._professional_match(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    personality_type = \"ENFJ\",\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5._df_files_MBTI_job_match, name = 'MBTI_ranking_fi_en', out = True)\n",
+    "\n",
+    "# Опционно\n",
+    "df = _b5.df_files_MBTI_job_match_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2297292e-1e4b-44e0-9c85-ab0fba999892",
+   "metadata": {},
+   "source": [
+    "### `MuPTA` (ru)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "3887d07c-eef2-4980-8d82-cabf6568aa7d",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:51:57</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:24:03</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1535,7 +2063,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:52:01</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:24:04</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1586,92 +2114,92 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758137</td>\n",
-       "      <td>0.693356</td>\n",
-       "      <td>0.650108</td>\n",
-       "      <td>0.744589</td>\n",
-       "      <td>0.488671</td>\n",
+       "      <td>0.765745</td>\n",
+       "      <td>0.696637</td>\n",
+       "      <td>0.656309</td>\n",
+       "      <td>0.75986</td>\n",
+       "      <td>0.494141</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.681602</td>\n",
-       "      <td>0.654339</td>\n",
-       "      <td>0.607156</td>\n",
-       "      <td>0.731282</td>\n",
-       "      <td>0.417908</td>\n",
+       "      <td>0.686514</td>\n",
+       "      <td>0.659488</td>\n",
+       "      <td>0.611838</td>\n",
+       "      <td>0.749739</td>\n",
+       "      <td>0.420672</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666104</td>\n",
-       "      <td>0.656836</td>\n",
-       "      <td>0.567863</td>\n",
-       "      <td>0.685067</td>\n",
-       "      <td>0.378102</td>\n",
+       "      <td>0.671993</td>\n",
+       "      <td>0.661216</td>\n",
+       "      <td>0.571759</td>\n",
+       "      <td>0.704542</td>\n",
+       "      <td>0.381026</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694171</td>\n",
-       "      <td>0.596195</td>\n",
-       "      <td>0.571414</td>\n",
-       "      <td>0.66223</td>\n",
-       "      <td>0.348639</td>\n",
+       "      <td>0.69828</td>\n",
+       "      <td>0.59893</td>\n",
+       "      <td>0.571893</td>\n",
+       "      <td>0.674907</td>\n",
+       "      <td>0.35082</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.712885</td>\n",
-       "      <td>0.594764</td>\n",
-       "      <td>0.571709</td>\n",
-       "      <td>0.716696</td>\n",
-       "      <td>0.37802</td>\n",
+       "      <td>0.718329</td>\n",
+       "      <td>0.598986</td>\n",
+       "      <td>0.573518</td>\n",
+       "      <td>0.73201</td>\n",
+       "      <td>0.379845</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664158</td>\n",
-       "      <td>0.670411</td>\n",
-       "      <td>0.60421</td>\n",
-       "      <td>0.696056</td>\n",
-       "      <td>0.399842</td>\n",
+       "      <td>0.670932</td>\n",
+       "      <td>0.671055</td>\n",
+       "      <td>0.602337</td>\n",
+       "      <td>0.708656</td>\n",
+       "      <td>0.399527</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761213</td>\n",
-       "      <td>0.652635</td>\n",
-       "      <td>0.651028</td>\n",
-       "      <td>0.788677</td>\n",
-       "      <td>0.459676</td>\n",
+       "      <td>0.767261</td>\n",
+       "      <td>0.658167</td>\n",
+       "      <td>0.653367</td>\n",
+       "      <td>0.801366</td>\n",
+       "      <td>0.463443</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.692788</td>\n",
-       "      <td>0.68324</td>\n",
-       "      <td>0.616737</td>\n",
-       "      <td>0.795205</td>\n",
-       "      <td>0.447242</td>\n",
+       "      <td>0.699837</td>\n",
+       "      <td>0.684907</td>\n",
+       "      <td>0.616671</td>\n",
+       "      <td>0.806437</td>\n",
+       "      <td>0.447853</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.705923</td>\n",
-       "      <td>0.658382</td>\n",
-       "      <td>0.610645</td>\n",
-       "      <td>0.697415</td>\n",
-       "      <td>0.411988</td>\n",
+       "      <td>0.710566</td>\n",
+       "      <td>0.66299</td>\n",
+       "      <td>0.610562</td>\n",
+       "      <td>0.711242</td>\n",
+       "      <td>0.413696</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753417</td>\n",
-       "      <td>0.708372</td>\n",
-       "      <td>0.654608</td>\n",
-       "      <td>0.816416</td>\n",
-       "      <td>0.504743</td>\n",
+       "      <td>0.759404</td>\n",
+       "      <td>0.712562</td>\n",
+       "      <td>0.658357</td>\n",
+       "      <td>0.830507</td>\n",
+       "      <td>0.507612</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1680,29 +2208,29 @@
       "text/plain": [
        "                               Path  Openness Conscientiousness Extraversion  \\\n",
        "Person ID                                                                      \n",
-       "1          speaker_01_center_83.mov  0.758137          0.693356     0.650108   \n",
-       "2          speaker_06_center_83.mov  0.681602          0.654339     0.607156   \n",
-       "3          speaker_07_center_83.mov  0.666104          0.656836     0.567863   \n",
-       "4          speaker_10_center_83.mov  0.694171          0.596195     0.571414   \n",
-       "5          speaker_11_center_83.mov  0.712885          0.594764     0.571709   \n",
-       "6          speaker_15_center_83.mov  0.664158          0.670411      0.60421   \n",
-       "7          speaker_19_center_83.mov  0.761213          0.652635     0.651028   \n",
-       "8          speaker_23_center_83.mov  0.692788           0.68324     0.616737   \n",
-       "9          speaker_24_center_83.mov  0.705923          0.658382     0.610645   \n",
-       "10         speaker_27_center_83.mov  0.753417          0.708372     0.654608   \n",
+       "1          speaker_01_center_83.mov  0.765745          0.696637     0.656309   \n",
+       "2          speaker_06_center_83.mov  0.686514          0.659488     0.611838   \n",
+       "3          speaker_07_center_83.mov  0.671993          0.661216     0.571759   \n",
+       "4          speaker_10_center_83.mov   0.69828           0.59893     0.571893   \n",
+       "5          speaker_11_center_83.mov  0.718329          0.598986     0.573518   \n",
+       "6          speaker_15_center_83.mov  0.670932          0.671055     0.602337   \n",
+       "7          speaker_19_center_83.mov  0.767261          0.658167     0.653367   \n",
+       "8          speaker_23_center_83.mov  0.699837          0.684907     0.616671   \n",
+       "9          speaker_24_center_83.mov  0.710566           0.66299     0.610562   \n",
+       "10         speaker_27_center_83.mov  0.759404          0.712562     0.658357   \n",
        "\n",
        "          Agreeableness Non-Neuroticism  \n",
        "Person ID                                \n",
-       "1              0.744589        0.488671  \n",
-       "2              0.731282        0.417908  \n",
-       "3              0.685067        0.378102  \n",
-       "4               0.66223        0.348639  \n",
-       "5              0.716696         0.37802  \n",
-       "6              0.696056        0.399842  \n",
-       "7              0.788677        0.459676  \n",
-       "8              0.795205        0.447242  \n",
-       "9              0.697415        0.411988  \n",
-       "10             0.816416        0.504743  "
+       "1               0.75986        0.494141  \n",
+       "2              0.749739        0.420672  \n",
+       "3              0.704542        0.381026  \n",
+       "4              0.674907         0.35082  \n",
+       "5               0.73201        0.379845  \n",
+       "6              0.708656        0.399527  \n",
+       "7              0.801366        0.463443  \n",
+       "8              0.806437        0.447853  \n",
+       "9              0.711242        0.413696  \n",
+       "10             0.830507        0.507612  "
       ]
      },
      "metadata": {},
@@ -1711,7 +2239,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:52:01</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:24:04</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1761,21 +2289,21 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MAE</th>\n",
-       "      <td>0.0673</td>\n",
-       "      <td>0.0789</td>\n",
-       "      <td>0.1325</td>\n",
-       "      <td>0.102</td>\n",
+       "      <td>0.0706</td>\n",
+       "      <td>0.0788</td>\n",
+       "      <td>0.1328</td>\n",
+       "      <td>0.1071</td>\n",
        "      <td>0.1002</td>\n",
-       "      <td>0.0962</td>\n",
+       "      <td>0.0979</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.9327</td>\n",
-       "      <td>0.9211</td>\n",
-       "      <td>0.8675</td>\n",
-       "      <td>0.898</td>\n",
+       "      <td>0.9294</td>\n",
+       "      <td>0.9212</td>\n",
+       "      <td>0.8672</td>\n",
+       "      <td>0.8929</td>\n",
        "      <td>0.8998</td>\n",
-       "      <td>0.9038</td>\n",
+       "      <td>0.9021</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1784,13 +2312,13 @@
       "text/plain": [
        "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
        "Metrics                                                              \n",
-       "MAE         0.0673             0.0789        0.1325          0.102   \n",
-       "Accuracy    0.9327             0.9211        0.8675          0.898   \n",
+       "MAE         0.0706             0.0788        0.1328         0.1071   \n",
+       "Accuracy    0.9294             0.9212        0.8672         0.8929   \n",
        "\n",
        "          Non-Neuroticism    Mean  \n",
        "Metrics                            \n",
-       "MAE                0.1002  0.0962  \n",
-       "Accuracy           0.8998  0.9038  "
+       "MAE                0.1002  0.0979  \n",
+       "Accuracy           0.8998  0.9021  "
       ]
      },
      "metadata": {},
@@ -1799,7 +2327,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 18:52:01</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0962</span>, средняя точность: <span style=\"color:#1776D2\">0.9038</span> ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:24:04</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0979</span>, средняя точность: <span style=\"color:#1776D2\">0.9021</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1823,7 +2351,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 415.41 сек. ---**</span>"
+       "<span style=\"color:#666\">**--- Время выполнения: 322.244 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1838,7 +2366,7 @@
        "True"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1865,11 +2393,11 @@
     "res_load_model_nn = _b5.load_audio_model_nn()\n",
     "\n",
     "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование видеомоделей\n",
     "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
@@ -1877,37 +2405,37 @@
     "res_load_model_nn = _b5.load_video_model_nn()\n",
     "\n",
     "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
     "res_load_text_features = _b5.load_text_features()\n",
     "\n",
     "# Формирование текстовых моделей \n",
     "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
-    "res_setup_translation_model = _b5.setup_bert_encoder()\n",
+    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
     "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
     "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
     "\n",
     "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование модели для мультимодального объединения информации\n",
     "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
     "\n",
     "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
     "\n",
     "PATH_TO_DIR = './video_MuPTA/'\n",
     "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
@@ -1938,7 +2466,7 @@
     "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
     "\n",
     "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "url_accuracy = _b5.true_traits_['mupta']['googledisk']\n",
     "\n",
     "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
    ]
@@ -1963,7 +2491,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "id": "f79ba8a2-c173-4d83-9cf7-d0c991c7bcc0",
    "metadata": {},
    "outputs": [
@@ -2073,7 +2601,7 @@
        "5              5             15               15  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2100,7 +2628,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "id": "16e43257-3500-4dd8-b04a-34f7435fc185",
    "metadata": {},
    "outputs": [
@@ -2148,102 +2676,102 @@
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>71.387</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>72.022</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>70.057</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>70.828</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
        "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>69.831</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>70.475</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
        "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>66.608</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>67.163</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
        "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>64.866</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>65.400</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>64.169</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>64.833</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>63.845</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>64.447</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
        "      <td>0.400</td>\n",
-       "      <td>62.724</td>\n",
+       "      <td>63.247</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>61.945</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>62.660</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
-       "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>61.672</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>62.143</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -2252,32 +2780,32 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505   \n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489   \n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460   \n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447   \n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412   \n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418   \n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378   \n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400   \n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378   \n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
        "\n",
        "           Candidate score  \n",
        "Person ID                   \n",
-       "10                  71.387  \n",
-       "1                   70.057  \n",
-       "7                   69.831  \n",
-       "8                   66.608  \n",
-       "9                   64.866  \n",
-       "2                   64.169  \n",
-       "5                   63.845  \n",
-       "6                   62.724  \n",
-       "3                   61.945  \n",
-       "4                   61.672  "
+       "10                  72.022  \n",
+       "1                   70.828  \n",
+       "7                   70.475  \n",
+       "8                   67.163  \n",
+       "9                   65.400  \n",
+       "2                   64.833  \n",
+       "5                   64.447  \n",
+       "6                   63.247  \n",
+       "3                   62.660  \n",
+       "4                   62.143  "
       ]
      },
-     "execution_count": 11,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2314,7 +2842,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 15,
    "id": "41e60b73-f8a0-444d-a696-2f83ff138e53",
    "metadata": {},
    "outputs": [
@@ -2362,102 +2890,102 @@
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>72.930</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>73.659</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>70.172</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>70.980</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
        "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>69.985</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>70.703</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
        "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>69.649</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>70.152</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>66.261</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>67.153</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
        "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>65.774</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>66.427</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
        "      <td>0.400</td>\n",
-       "      <td>65.371</td>\n",
+       "      <td>65.843</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>63.941</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>64.840</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>63.477</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>64.202</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
-       "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>61.461</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>62.016</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -2466,32 +2994,32 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505   \n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489   \n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460   \n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447   \n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418   \n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412   \n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400   \n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378   \n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378   \n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
        "\n",
        "           Candidate score  \n",
        "Person ID                   \n",
-       "10                  72.930  \n",
-       "1                   70.172  \n",
-       "7                   69.985  \n",
-       "8                   69.649  \n",
-       "2                   66.261  \n",
-       "9                   65.774  \n",
-       "6                   65.371  \n",
-       "3                   63.941  \n",
-       "5                   63.477  \n",
-       "4                   61.461  "
+       "10                  73.659  \n",
+       "1                   70.980  \n",
+       "7                   70.703  \n",
+       "8                   70.152  \n",
+       "2                   67.153  \n",
+       "9                   66.427  \n",
+       "6                   65.843  \n",
+       "3                   64.840  \n",
+       "5                   64.202  \n",
+       "4                   62.016  "
       ]
      },
-     "execution_count": 12,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2551,7 +3079,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 16,
    "id": "1b7cae2f-76d6-4628-acfc-54d2f941113a",
    "metadata": {},
    "outputs": [
@@ -2716,7 +3244,7 @@
        "10        0.238  "
       ]
      },
-     "execution_count": 13,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2735,7 +3263,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 17,
    "id": "0921b47e-003c-41a6-9fd0-ff1a4b434f70",
    "metadata": {},
    "outputs": [
@@ -2789,64 +3317,77 @@
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>0.442</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.525</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>0.447</td>\n",
+       "      <td>0.474</td>\n",
+       "      <td>0.657</td>\n",
+       "      <td>0.531</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
        "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>0.384</td>\n",
-       "      <td>0.391</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>0.455</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.387</td>\n",
+       "      <td>0.394</td>\n",
+       "      <td>0.559</td>\n",
+       "      <td>0.459</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
        "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>0.379</td>\n",
-       "      <td>0.386</td>\n",
-       "      <td>0.553</td>\n",
-       "      <td>0.454</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>0.383</td>\n",
+       "      <td>0.390</td>\n",
+       "      <td>0.559</td>\n",
+       "      <td>0.459</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.389</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>0.455</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.382</td>\n",
+       "      <td>0.393</td>\n",
+       "      <td>0.560</td>\n",
+       "      <td>0.460</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>0.360</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>0.366</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.533</td>\n",
+       "      <td>0.437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>0.357</td>\n",
        "      <td>0.369</td>\n",
        "      <td>0.525</td>\n",
        "      <td>0.430</td>\n",
@@ -2854,67 +3395,54 @@
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
        "      <td>0.400</td>\n",
-       "      <td>0.354</td>\n",
-       "      <td>0.365</td>\n",
-       "      <td>0.517</td>\n",
-       "      <td>0.423</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
-       "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>0.353</td>\n",
-       "      <td>0.365</td>\n",
-       "      <td>0.520</td>\n",
-       "      <td>0.425</td>\n",
+       "      <td>0.357</td>\n",
+       "      <td>0.368</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>0.427</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>0.346</td>\n",
-       "      <td>0.359</td>\n",
-       "      <td>0.508</td>\n",
-       "      <td>0.416</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>0.352</td>\n",
+       "      <td>0.364</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.423</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>0.343</td>\n",
-       "      <td>0.352</td>\n",
-       "      <td>0.503</td>\n",
-       "      <td>0.413</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>0.347</td>\n",
+       "      <td>0.356</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.418</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
-       "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>0.328</td>\n",
-       "      <td>0.339</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.397</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>0.332</td>\n",
+       "      <td>0.343</td>\n",
+       "      <td>0.490</td>\n",
+       "      <td>0.401</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -2923,32 +3451,32 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505   \n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447   \n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460   \n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489   \n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418   \n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400   \n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412   \n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378   \n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378   \n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
        "\n",
        "           Analytical  Interactive  Routine  Non-Routine  \n",
        "Person ID                                                 \n",
-       "10              0.442        0.469    0.650        0.525  \n",
-       "8               0.384        0.391    0.554        0.455  \n",
-       "7               0.379        0.386    0.553        0.454  \n",
-       "1               0.377        0.389    0.554        0.455  \n",
-       "2               0.360        0.369    0.525        0.430  \n",
-       "6               0.354        0.365    0.517        0.423  \n",
-       "9               0.353        0.365    0.520        0.425  \n",
-       "3               0.346        0.359    0.508        0.416  \n",
-       "5               0.343        0.352    0.503        0.413  \n",
-       "4               0.328        0.339    0.485        0.397  "
+       "10              0.447        0.474    0.657        0.531  \n",
+       "8               0.387        0.394    0.559        0.459  \n",
+       "7               0.383        0.390    0.559        0.459  \n",
+       "1               0.382        0.393    0.560        0.460  \n",
+       "2               0.366        0.374    0.533        0.437  \n",
+       "9               0.357        0.369    0.525        0.430  \n",
+       "6               0.357        0.368    0.522        0.427  \n",
+       "3               0.352        0.364    0.515        0.423  \n",
+       "5               0.347        0.356    0.510        0.418  \n",
+       "4               0.332        0.343    0.490        0.401  "
       ]
      },
-     "execution_count": 14,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2971,42 +3499,144 @@
   },
   {
    "cell_type": "markdown",
-   "id": "708fcd2b-eb78-4f58-96d2-19298b8c26d9",
+   "id": "f443f6ad",
    "metadata": {},
    "source": [
-    "### `MuPTA` (en)"
+    "<hr>\n",
+    "\n",
+    "Для ранжирования кандидатов по одному из шестнадцати типов личности MBTI необходимо задать матрицу корреляции между персональными качествами личности человека и четырьмя диспозициями MBTI, установить порог полярности качеств и указать целевой тип личности MBTI.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции, представленных в статье [1]. Описание типов личности MBTI и соотвествующие им успешные профессии представлены в статье [2].\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "2) Tieger P.D., Barron B., Tieger K. Do what you are: Discover the perfect career for you through the secrets of personality type // Hachette UK. - 2024.\n",
+    "\n",
+    "##### Типы личности MBTI основаны на четырех измерениях личности:\n",
+    "\n",
+    "<div style=\"text-align: center;\">\n",
+    "  <table style=\"width:100%; margin: 0 auto; font-size: 0.6em;\">\n",
+    "    <tr>\n",
+    "      <th>Описание измерения</th>\n",
+    "      <th>Измерение</th>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Как мы взаимодействуем с миром и куда направляем свою энергию</td>\n",
+    "      <td>(E) Экстраверсия - Интроверсия (I)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Вид информации, которую мы естественным образом замечаем</td>\n",
+    "      <td>(S) Сенсорика - Интуиция (N)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Как мы принимаем решения</td>\n",
+    "      <td>(T) Логика - Чувства (F)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Предпочитаем ли мы жить более структурированно (принимая решения) или более спонтанно (принимая информацию)</td>\n",
+    "      <td>(J) Оценка - Восприятие (P)</td>\n",
+    "    </tr>\n",
+    "  </table>\n",
+    "</div>\n",
+    "\n",
+    "##### Типы личности MBTI и соотвествующие им успешные профессии:\n",
+    "\n",
+    "<div style=\"text-align: center;\">\n",
+    "  <table style=\"width: 100%; margin: 0 auto; font-size: 0.6em;\">\n",
+    "    <tr>\n",
+    "      <th>Тип личности</th>\n",
+    "      <th>Описание</th>\n",
+    "      <th>Успешные профессии</th>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISTJ</td>\n",
+    "      <td>Этот человек отличается ответственностью, строгостью и педантичностью. Он опирается на объективные факты и склонен к аналитическому мышлению. Приступает к задаче только тогда, когда уверен в своих возможностях и успехе</td>\n",
+    "      <td>Инспектор: бухгалтер, аудитор, бюджетный аналитик, финансовый менеджер, разработчик, системный аналитик, библиотекарь и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISFJ</td>\n",
+    "      <td>Этот человек склонен к самоанализу и анализу окружающих, легко распознает фальшь и предпочитает сохранять психологическую дистанцию. Он исполнителен, внимателен и готов помогать другим. Его силы и энергия исходят из внутренних ресурсов, и он всегда полагается на собственный опыт</td>\n",
+    "      <td>Защитник: медсестра, врач, ветеринар или ветеринарный ассистент, социальный работник, сельскохозяйственный или пищевой ученый, секретарь, водитель и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INFJ</td>\n",
+    "      <td>О таких людях говорят: «ему можно доверять». Он отличается высокой чувствительностью, уделяет большое внимание межличностным отношениям, умеет давать ценные советы и помогает раскрывать потенциал других. Развитая интуиция не только генерирует множество идей, но и способствует самоорганизации</td>\n",
+    "      <td>Советник: психолог, специалист по управлению персоналом, офис-менеджер, специалист по обучению, графический дизайнер и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INTJ</td>\n",
+    "      <td>Этот человек умеет выделять главное, говорит четко и по существу, придерживается практического подхода. Он стремится постоянно улучшать свою работу и всегда ищет способы сделать задачу еще лучше. Пустые разговоры ему не по душе, поэтому он избегает больших шумных компаний и с трудом заводит новые знакомства</td>\n",
+    "      <td>Мастермайнд: аниматор, архитектор, копирайтер, фотограф, тележурналист, видеомонтажер, специалист по бизнес-развитию, исполнительный директор, профессор и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISTP</td>\n",
+    "      <td>Этот человек воспринимает мир через ощущения. По природе эмпат, но чаще сосредоточен на себе. Его умение объективно принимать решения и анализировать ситуацию указывает на технический склад ума. Он всегда соблюдает дедлайны, хотя иногда может поступить неожиданно</td>\n",
+    "      <td>Создатель: инженер, техник, строитель, инспектор, судебный эксперт, программист, разработчик ПО и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISFP</td>\n",
+    "      <td>Этот человек умеет находить радость в однообразии и рутинных делах. Прекрасно ладит с людьми, избегая конфликтов. Ему важно чувствовать свою значимость и оказывать помощь. Такой человек не стремится руководить или менять других, уважает их личные границы и ожидает того же в ответ. По натуре он приземленный практик, на которого всегда можно положиться</td>\n",
+    "      <td>Композитор: помощник по маркетингу, танцор, шеф-повар, офис-администратор, художник, дизайнер интерьеров, секретарь, медсестра и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INFP</td>\n",
+    "      <td>Этот человек - чувствительный лирик, прекрасно разбирающийся в людях и легко вызывающий у них симпатию. Он обладает отличным чувством юмора и уделяет большое внимание своему внешнему виду. Стремится к самопознанию, гармонии с собой и старается быть полезным окружающим</td>\n",
+    "      <td>Целитель: писатель, дизайнер мультимедиа, менеджер по работе с клиентами, учитель для детей с особыми потребностями, тренер, редактор, модельер и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INTP</td>\n",
+    "      <td>Этот человек - эрудит с философским складом ума. Он тщательно анализирует свои решения, стремясь к объективности и беспристрастности. Бурные проявления эмоций ему не свойственны. Однако большое количество данных и их изменчивость могут вызывать у него внутреннее напряжение</td>\n",
+    "      <td>Архитектор: технический писатель, веб-разработчик, аналитик информационной безопасности, исследователь, ученый, юрист и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESTP</td>\n",
+    "      <td>Этот человек всегда добивается успеха, невзирая на препятствия, которые лишь усиливают его целеустремленность. Он стремится к лидерским позициям и плохо переносит роль подчиненного. Обычно разрабатывает четкий план действий и неуклонно ему следует</td>\n",
+    "      <td>Промоутер: специалист по работе с клиентами, актер, личный тренер, бренд-амбассадор, менеджер, предприниматель, креативный директор, полицейский, маркетолог, производитель и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESFP</td>\n",
+    "      <td>Этот человек легко выявляет слабые стороны людей, что позволяет ему эффективно манипулировать и управлять. В общении он чаще всего руководствуется собственными интересами и предпочитает жить в настоящем. Часто не завершает начатое, стремясь к быстрым результатам. Однако при этом стремится поддерживать гармоничные отношения с окружающими</td>\n",
+    "      <td>Исполнитель: бортпроводник, артист, учитель, менеджер по связям с общественностью, торговый представитель, организатор мероприятий и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ENFP</td>\n",
+    "      <td>Этот человек - творческая личность и фантазер, обладающий качествами, которые помогают ему успешно взаимодействовать с другими, быть открытым и общительным. Он активно участвует в различных мероприятиях, легко решает возникающие вопросы и демонстрирует гибкость</td>\n",
+    "      <td>Чемпион: медицинский работник, продюсер, продавец-консультант, специалист по обслуживанию клиентов, сценарист, ведущий на ТВ/радио и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ENTP</td>\n",
+    "      <td>Этот человек - изобретательный, инициативный и гибкий. Он генератор идей и первопроходец, который не выносит рутины. Постоянное движение и интуитивное принятие решений всегда сопровождают его в работе</td>\n",
+    "      <td>Новатор: инженер, маркетолог, менеджер по социальным сетям, аналитик управления, руководитель цифрового маркетинга, бизнес-консультант, разработчик игр, менеджер по продажам и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESTJ</td>\n",
+    "      <td>Это трудолюбивый человек, который воспринимает мир таким, какой он есть. Он склонен тщательно планировать и доводить дела до конца. Заботится о своем ближайшем окружении, проявляет добродушие, но иногда может быть вспыльчивым, резким и упрямым</td>\n",
+    "      <td>Супервайзер: управляющий директор, менеджер отеля, финансовый сотрудник, судья, агент по недвижимости, генеральный директор, шеф-повар, менеджер по бизнес-развитию, телемаркетолог и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESFJ</td>\n",
+    "      <td>Этот человек умеет оказывать влияние на людей, проявляет заботу и готов жертвовать собой ради других. Он легко устанавливает контакт с любым человеком и способен направить ситуацию в нужное ему русло</td>\n",
+    "      <td>Поставщик: специалист по технической поддержке, менеджер по работе с клиентами, профессор колледжа, медицинский исследователь, бухгалтер, фотожурналист и т. д.</td>\n",
+    "    </tr>\n",
+    "    <td>ENFJ</td>\n",
+    "      <td>Этот человек отличается эмоциональностью и эмпатией. Его мимика выразительна, а речь — красноречива. Благодаря своей самоорганизованности, он успешно воплощает свои фантазии и идеи в жизнь. Он интуитивно понимает, какое решение следует принять в каждой конкретной ситуации</td>\n",
+    "      <td>Учитель: менеджер по связям с общественностью, менеджер по продажам, директор по управлению персоналом, арт-директор, консультант и т. д.</td>\n",
+    "    </tr>\n",
+    "    <td>ENTJ</td>\n",
+    "      <td>Этот человек легко увлекается, готов рисковать и полагается на интуицию. Без страха внедряет новые технологии и способен глубоко анализировать как себя, так и окружающий мир. Жизнь для него - это борьба, в которой он чувствует себя уверенно. Открыт для новых возможностей, но при этом нуждается в контроле</td>\n",
+    "      <td>Командир: руководитель строительства, администратор службы здравоохранения, финансовый бухгалтер, аудитор, юрист, директор школы, химический инженер, менеджер баз данных и т. д.</td>\n",
+    "    </tr>\n",
+    "  </table>\n",
+    "</div>\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции и ранжировать кандидатов по другим типам личности."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "id": "1b1f1294-6f09-4827-85c6-75ccc7fbd375",
+   "execution_count": 18,
+   "id": "f3ab3951",
    "metadata": {},
    "outputs": [
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@@ -3028,16 +3658,14 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
-       "      <th></th>\n",
+       "      <th>ID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -3048,141 +3676,81 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.564985</td>\n",
-       "      <td>0.539052</td>\n",
-       "      <td>0.440615</td>\n",
-       "      <td>0.59251</td>\n",
-       "      <td>0.488763</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.14</td>\n",
+       "      <td>-0.16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.650774</td>\n",
-       "      <td>0.663849</td>\n",
-       "      <td>0.607308</td>\n",
-       "      <td>0.643847</td>\n",
-       "      <td>0.620627</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>-0.04</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.435976</td>\n",
-       "      <td>0.486683</td>\n",
-       "      <td>0.313828</td>\n",
-       "      <td>0.415446</td>\n",
-       "      <td>0.396618</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.07</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.498542</td>\n",
-       "      <td>0.511243</td>\n",
-       "      <td>0.412592</td>\n",
-       "      <td>0.468947</td>\n",
-       "      <td>0.44399</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>-0.35</td>\n",
+       "      <td>0.03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.394776</td>\n",
-       "      <td>0.341608</td>\n",
-       "      <td>0.327082</td>\n",
-       "      <td>0.427304</td>\n",
-       "      <td>0.354936</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566107</td>\n",
-       "      <td>0.543811</td>\n",
-       "      <td>0.492766</td>\n",
-       "      <td>0.587411</td>\n",
-       "      <td>0.499433</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506271</td>\n",
-       "      <td>0.438215</td>\n",
-       "      <td>0.430894</td>\n",
-       "      <td>0.456177</td>\n",
-       "      <td>0.44075</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486463</td>\n",
-       "      <td>0.521755</td>\n",
-       "      <td>0.309894</td>\n",
-       "      <td>0.432291</td>\n",
-       "      <td>0.433601</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417404</td>\n",
-       "      <td>0.473339</td>\n",
-       "      <td>0.320714</td>\n",
-       "      <td>0.445086</td>\n",
-       "      <td>0.414649</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526112</td>\n",
-       "      <td>0.661107</td>\n",
-       "      <td>0.443167</td>\n",
-       "      <td>0.558965</td>\n",
-       "      <td>0.554224</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path  Openness Conscientiousness Extraversion  \\\n",
-       "Person ID                                                                      \n",
-       "1          speaker_01_center_83.mov  0.564985          0.539052     0.440615   \n",
-       "2          speaker_06_center_83.mov  0.650774          0.663849     0.607308   \n",
-       "3          speaker_07_center_83.mov  0.435976          0.486683     0.313828   \n",
-       "4          speaker_10_center_83.mov  0.498542          0.511243     0.412592   \n",
-       "5          speaker_11_center_83.mov  0.394776          0.341608     0.327082   \n",
-       "6          speaker_15_center_83.mov  0.566107          0.543811     0.492766   \n",
-       "7          speaker_19_center_83.mov  0.506271          0.438215     0.430894   \n",
-       "8          speaker_23_center_83.mov  0.486463          0.521755     0.309894   \n",
-       "9          speaker_24_center_83.mov  0.417404          0.473339     0.320714   \n",
-       "10         speaker_27_center_83.mov  0.526112          0.661107     0.443167   \n",
-       "\n",
-       "          Agreeableness Non-Neuroticism  \n",
-       "Person ID                                \n",
-       "1               0.59251        0.488763  \n",
-       "2              0.643847        0.620627  \n",
-       "3              0.415446        0.396618  \n",
-       "4              0.468947         0.44399  \n",
-       "5              0.427304        0.354936  \n",
-       "6              0.587411        0.499433  \n",
-       "7              0.456177         0.44075  \n",
-       "8              0.432291        0.433601  \n",
-       "9              0.445086        0.414649  \n",
-       "10             0.558965        0.554224  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:00:52</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
+       "                Trait    EI    SN    TF    JP\n",
+       "ID                                           \n",
+       "1            Openness  0.09 -0.03 -0.14 -0.16\n",
+       "2   Conscientiousness  0.04 -0.04  0.20  0.14\n",
+       "3        Extraversion  0.20 -0.03  0.01 -0.07\n",
+       "4       Agreeableness  0.02  0.05 -0.35  0.03\n",
+       "5     Non-Neuroticism  0.08  0.00  0.16  0.00"
       ]
      },
+     "execution_count": 18,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "\n",
+    "df_correlation_coefficients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "3743bc4e",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -3204,15 +3772,29 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
-       "      <th>Mean</th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>MBTI_Score</th>\n",
+       "      <th>Match</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Metrics</th>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -3223,46 +3805,249 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>MAE</th>\n",
-       "      <td>0.1727</td>\n",
-       "      <td>0.1672</td>\n",
-       "      <td>0.1661</td>\n",
-       "      <td>0.2579</td>\n",
-       "      <td>0.107</td>\n",
-       "      <td>0.1742</td>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>0.205006</td>\n",
+       "      <td>-0.028877</td>\n",
+       "      <td>-0.323879</td>\n",
+       "      <td>-0.052313</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.418321</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Accuracy</th>\n",
-       "      <td>0.8273</td>\n",
-       "      <td>0.8328</td>\n",
-       "      <td>0.8339</td>\n",
-       "      <td>0.7421</td>\n",
-       "      <td>0.893</td>\n",
-       "      <td>0.8258</td>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.203710</td>\n",
+       "      <td>-0.032534</td>\n",
+       "      <td>-0.306328</td>\n",
+       "      <td>-0.048136</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.406929</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
-       "Metrics                                                              \n",
-       "MAE         0.1727             0.1672        0.1661         0.2579   \n",
-       "Accuracy    0.8273             0.8328        0.8339         0.7421   \n",
-       "\n",
-       "          Non-Neuroticism    Mean  \n",
-       "Metrics                            \n",
-       "MAE                 0.107  0.1742  \n",
-       "Accuracy            0.893  0.8258  "
-      ]
-     },
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.194016</td>\n",
+       "      <td>-0.026570</td>\n",
+       "      <td>-0.308738</td>\n",
+       "      <td>-0.035061</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.396993</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>0.191874</td>\n",
+       "      <td>-0.027843</td>\n",
+       "      <td>-0.287812</td>\n",
+       "      <td>-0.037850</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.380647</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>0.187565</td>\n",
+       "      <td>-0.026114</td>\n",
+       "      <td>-0.292012</td>\n",
+       "      <td>-0.049261</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.379269</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>0.193712</td>\n",
+       "      <td>-0.030591</td>\n",
+       "      <td>-0.275902</td>\n",
+       "      <td>-0.042274</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.375154</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>0.189904</td>\n",
+       "      <td>-0.029607</td>\n",
+       "      <td>-0.265650</td>\n",
+       "      <td>-0.034305</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.363871</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>0.285739</td>\n",
+       "      <td>-0.029510</td>\n",
+       "      <td>-0.166680</td>\n",
+       "      <td>-0.042916</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.361447</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>0.186613</td>\n",
+       "      <td>-0.028317</td>\n",
+       "      <td>-0.264603</td>\n",
+       "      <td>-0.047660</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.359650</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>0.184889</td>\n",
+       "      <td>-0.028534</td>\n",
+       "      <td>-0.263672</td>\n",
+       "      <td>-0.033835</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.357821</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "\n",
+       "                 EI        SN        TF        JP  MBTI  MBTI_Score  Match  \n",
+       "Person ID                                                                   \n",
+       "7          0.205006 -0.028877 -0.323879 -0.052313  ENFP    0.418321   75.0  \n",
+       "1          0.203710 -0.032534 -0.306328 -0.048136  ENFP    0.406929   75.0  \n",
+       "8          0.194016 -0.026570 -0.308738 -0.035061  ENFP    0.396993   75.0  \n",
+       "2          0.191874 -0.027843 -0.287812 -0.037850  ENFP    0.380647   75.0  \n",
+       "5          0.187565 -0.026114 -0.292012 -0.049261  ENFP    0.379269   75.0  \n",
+       "9          0.193712 -0.030591 -0.275902 -0.042274  ENFP    0.375154   75.0  \n",
+       "6          0.189904 -0.029607 -0.265650 -0.034305  ENFP    0.363871   75.0  \n",
+       "10         0.285739 -0.029510 -0.166680 -0.042916  ENFP    0.361447   75.0  \n",
+       "4          0.186613 -0.028317 -0.264603 -0.047660  ENFP    0.359650   75.0  \n",
+       "3          0.184889 -0.028534 -0.263672 -0.033835  ENFP    0.357821   75.0  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._professional_match(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    personality_type = \"ENFJ\",\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5._df_files_MBTI_job_match, name = 'MBTI_ranking_mupta_ru', out = True)\n",
+    "\n",
+    "# Опционно\n",
+    "df = _b5.df_files_MBTI_job_match_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "708fcd2b-eb78-4f58-96d2-19298b8c26d9",
+   "metadata": {},
+   "source": [
+    "### `MuPTA` (en)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "1b1f1294-6f09-4827-85c6-75ccc7fbd375",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:40:54</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
      "metadata": {},
      "output_type": "display_data"
     },
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:00:52</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.1742</span>, средняя точность: <span style=\"color:#1776D2\">0.8258</span> ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:40:55</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -3271,10 +4056,174 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.59561</td>\n",
+       "      <td>0.542967</td>\n",
+       "      <td>0.440668</td>\n",
+       "      <td>0.589769</td>\n",
+       "      <td>0.515306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661347</td>\n",
+       "      <td>0.673973</td>\n",
+       "      <td>0.603208</td>\n",
+       "      <td>0.64543</td>\n",
+       "      <td>0.6431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.439868</td>\n",
+       "      <td>0.465049</td>\n",
+       "      <td>0.284547</td>\n",
+       "      <td>0.422551</td>\n",
+       "      <td>0.396058</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.47715</td>\n",
+       "      <td>0.502563</td>\n",
+       "      <td>0.373686</td>\n",
+       "      <td>0.441372</td>\n",
+       "      <td>0.424637</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403292</td>\n",
+       "      <td>0.344359</td>\n",
+       "      <td>0.317304</td>\n",
+       "      <td>0.422228</td>\n",
+       "      <td>0.384346</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.581837</td>\n",
+       "      <td>0.562177</td>\n",
+       "      <td>0.504623</td>\n",
+       "      <td>0.602169</td>\n",
+       "      <td>0.522254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510444</td>\n",
+       "      <td>0.448468</td>\n",
+       "      <td>0.425599</td>\n",
+       "      <td>0.451861</td>\n",
+       "      <td>0.447891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.500526</td>\n",
+       "      <td>0.541376</td>\n",
+       "      <td>0.308529</td>\n",
+       "      <td>0.441178</td>\n",
+       "      <td>0.452412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.427677</td>\n",
+       "      <td>0.511355</td>\n",
+       "      <td>0.301078</td>\n",
+       "      <td>0.434281</td>\n",
+       "      <td>0.442301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566414</td>\n",
+       "      <td>0.659169</td>\n",
+       "      <td>0.434059</td>\n",
+       "      <td>0.59122</td>\n",
+       "      <td>0.579172</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path  Openness Conscientiousness Extraversion  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov   0.59561          0.542967     0.440668   \n",
+       "2          speaker_06_center_83.mov  0.661347          0.673973     0.603208   \n",
+       "3          speaker_07_center_83.mov  0.439868          0.465049     0.284547   \n",
+       "4          speaker_10_center_83.mov   0.47715          0.502563     0.373686   \n",
+       "5          speaker_11_center_83.mov  0.403292          0.344359     0.317304   \n",
+       "6          speaker_15_center_83.mov  0.581837          0.562177     0.504623   \n",
+       "7          speaker_19_center_83.mov  0.510444          0.448468     0.425599   \n",
+       "8          speaker_23_center_83.mov  0.500526          0.541376     0.308529   \n",
+       "9          speaker_24_center_83.mov  0.427677          0.511355     0.301078   \n",
+       "10         speaker_27_center_83.mov  0.566414          0.659169     0.434059   \n",
+       "\n",
+       "          Agreeableness Non-Neuroticism  \n",
+       "Person ID                                \n",
+       "1              0.589769        0.515306  \n",
+       "2               0.64543          0.6431  \n",
+       "3              0.422551        0.396058  \n",
+       "4              0.441372        0.424637  \n",
+       "5              0.422228        0.384346  \n",
+       "6              0.602169        0.522254  \n",
+       "7              0.451861        0.447891  \n",
+       "8              0.441178        0.452412  \n",
+       "9              0.434281        0.442301  \n",
+       "10              0.59122        0.579172  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:40:55</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -3283,10 +4232,86 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Metrics</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>MAE</th>\n",
+       "      <td>0.1632</td>\n",
+       "      <td>0.1621</td>\n",
+       "      <td>0.176</td>\n",
+       "      <td>0.2589</td>\n",
+       "      <td>0.1122</td>\n",
+       "      <td>0.1745</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Accuracy</th>\n",
+       "      <td>0.8368</td>\n",
+       "      <td>0.8379</td>\n",
+       "      <td>0.824</td>\n",
+       "      <td>0.7411</td>\n",
+       "      <td>0.8878</td>\n",
+       "      <td>0.8255</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
+       "Metrics                                                              \n",
+       "MAE         0.1632             0.1621         0.176         0.2589   \n",
+       "Accuracy    0.8368             0.8379         0.824         0.7411   \n",
+       "\n",
+       "          Non-Neuroticism    Mean  \n",
+       "Metrics                            \n",
+       "MAE                0.1122  0.1745  \n",
+       "Accuracy           0.8878  0.8255  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 372.823 сек. ---**</span>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 17:40:55</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.1745</span>, средняя точность: <span style=\"color:#1776D2\">0.8255</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -3297,13 +4322,37 @@
     },
     {
      "data": {
+      "text/markdown": [
+       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
+      ],
       "text/plain": [
-       "True"
+       "<IPython.core.display.Markdown object>"
       ]
      },
-     "execution_count": 15,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**--- Время выполнения: 316.051 сек. ---**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -3328,11 +4377,11 @@
     "res_load_model_nn = _b5.load_audio_model_nn()\n",
     "\n",
     "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование видеомоделей\n",
     "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
@@ -3340,37 +4389,36 @@
     "res_load_model_nn = _b5.load_video_model_nn()\n",
     "\n",
     "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
     "res_load_text_features = _b5.load_text_features()\n",
     "\n",
     "# Формирование текстовых моделей \n",
-    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
-    "res_setup_translation_model = _b5.setup_bert_encoder()\n",
+    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
     "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
     "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
     "\n",
     "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование модели для мультимодального объединения информации\n",
     "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
     "\n",
     "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
     "\n",
     "PATH_TO_DIR = './video_MuPTA/'\n",
     "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
@@ -3396,38 +4444,389 @@
     "for curr_files in tets_name_files:\n",
     "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
     "\n",
-    "# Получение прогнозов\n",
-    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
-    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "# Получение прогнозов\n",
+    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
+    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "\n",
+    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
+    "url_accuracy = _b5.true_traits_['mupta']['googledisk']\n",
+    "\n",
+    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7d2dceb-423d-463d-ba89-61603250689a",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "Для выполнения ранжирования кандидатов необходимо знать весовые коэффициенты, определяющие приоритетность персональных качеств личности в зависимости от профессии.\n",
+    "\n",
+    "Предлагаются весовые коэффициенты для 5 профессий, вычисленные на основе научных статей:\n",
+    "\n",
+    "1) Sajjad H. et al. Personality and Career Choices // African Journal of Business Management. - 2012. – Vol. 6 (6) – pp. 2255-2260.\n",
+    "2) Alkhelil A. H. The Relationship between Personality Traits and Career Choice: A Case Study of Secondary School Students // International Journal of Academic Research in Progressive Education and Development. – 2016. – Vol. 5(2). – pp. 2226-6348.\n",
+    "3) De Jong N. et al. Personality Traits and Career Role Enactment: Career Role Preferences as a Mediator // Frontiers in Psychology. – 2019. – Vol. 10. – pp. 1720.\n",
+    "\n",
+    "Пользователь может установить свои весовые коэффициенты; сумма весов должна быть равна 100."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "b38c6569-1558-447a-875d-5735451e8f26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Profession</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Managers/executives</td>\n",
+       "      <td>15</td>\n",
+       "      <td>35</td>\n",
+       "      <td>15</td>\n",
+       "      <td>30</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Entrepreneurship</td>\n",
+       "      <td>30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Social/Non profit making professions</td>\n",
+       "      <td>5</td>\n",
+       "      <td>5</td>\n",
+       "      <td>35</td>\n",
+       "      <td>35</td>\n",
+       "      <td>20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Public sector professions</td>\n",
+       "      <td>15</td>\n",
+       "      <td>50</td>\n",
+       "      <td>15</td>\n",
+       "      <td>15</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Scientists/researchers, and engineers</td>\n",
+       "      <td>50</td>\n",
+       "      <td>15</td>\n",
+       "      <td>5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Profession  Openness  Conscientiousness  \\\n",
+       "ID                                                                       \n",
+       "1                     Managers/executives        15                 35   \n",
+       "2                        Entrepreneurship        30                 30   \n",
+       "3    Social/Non profit making professions         5                  5   \n",
+       "4               Public sector professions        15                 50   \n",
+       "5   Scientists/researchers, and engineers        50                 15   \n",
+       "\n",
+       "    Extraversion  Agreeableness  Non-Neuroticism  \n",
+       "ID                                                \n",
+       "1             15             30                5  \n",
+       "2              5              5               30  \n",
+       "3             35             35               20  \n",
+       "4             15             15                5  \n",
+       "5              5             15               15  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с весовыми коэффициентами\n",
+    "url = 'https://download.sberdisk.ru/download/file/478675798?token=fF5fNZVpthQlEV0&filename=traits_priority_for_professions.csv'\n",
+    "traits_priority_for_professions = pd.read_csv(url)\n",
+    "\n",
+    "traits_priority_for_professions.index.name = 'ID'\n",
+    "traits_priority_for_professions.index += 1\n",
+    "traits_priority_for_professions.index = traits_priority_for_professions.index.map(str)\n",
+    "\n",
+    "traits_priority_for_professions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ece309a9-5818-435d-8721-b15e2eca8e01",
+   "metadata": {},
+   "source": [
+    "#### Ранжирование кандидатов на должность инженера-проектировщика"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "6d095685-fda4-4943-9a0f-d0463a39798c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Candidate score</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>65.521</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>57.934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>56.914</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>56.704</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>48.093</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>47.873</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>46.254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>43.708</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>42.671</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>39.015</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
+       "\n",
+       "           Candidate score  \n",
+       "Person ID                   \n",
+       "2                   65.521  \n",
+       "10                  57.934  \n",
+       "6                   56.914  \n",
+       "1                   56.704  \n",
+       "8                   48.093  \n",
+       "7                   47.873  \n",
+       "4                   46.254  \n",
+       "9                   43.708  \n",
+       "3                   42.671  \n",
+       "5                   39.015  "
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weights = traits_priority_for_professions.iloc[4].values[1:]\n",
+    "weights = list(map(int, weights))\n",
+    "\n",
+    "_b5._candidate_ranking(\n",
+    "    weigths_openness = weights[0], \n",
+    "    weigths_conscientiousness = weights[1],\n",
+    "    weigths_extraversion = weights[2],\n",
+    "    weigths_agreeableness = weights[3], \n",
+    "    weigths_non_neuroticism = weights[4],\n",
+    "    out = False\n",
+    ")\n",
     "\n",
-    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "_b5._save_logs(df = _b5.df_files_ranking_, name = 'engineer_candidate_ranking_mupta_en', out = True)\n",
     "\n",
-    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
+    "# Опционно\n",
+    "df = _b5.df_files_ranking_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "b7d2dceb-423d-463d-ba89-61603250689a",
+   "id": "d56b0166-8fe2-4995-87d7-97b123176e0c",
    "metadata": {},
    "source": [
-    "<hr>\n",
-    "\n",
-    "Для выполнения ранжирования кандидатов необходимо знать весовые коэффициенты, определяющие приоритетность персональных качеств личности в зависимости от профессии.\n",
-    "\n",
-    "Предлагаются весовые коэффициенты для 5 профессий, вычисленные на основе научных статей:\n",
-    "\n",
-    "1) Sajjad H. et al. Personality and Career Choices // African Journal of Business Management. - 2012. – Vol. 6 (6) – pp. 2255-2260.\n",
-    "2) Alkhelil A. H. The Relationship between Personality Traits and Career Choice: A Case Study of Secondary School Students // International Journal of Academic Research in Progressive Education and Development. – 2016. – Vol. 5(2). – pp. 2226-6348.\n",
-    "3) De Jong N. et al. Personality Traits and Career Role Enactment: Career Role Preferences as a Mediator // Frontiers in Psychology. – 2019. – Vol. 10. – pp. 1720.\n",
-    "\n",
-    "Пользователь может установить свои весовые коэффициенты; сумма весов должна быть равна 100."
+    "#### Ранжирование кандидатов на должность менеджера"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "id": "b38c6569-1558-447a-875d-5735451e8f26",
+   "execution_count": 24,
+   "id": "5f54009f-1bc5-49cf-8f33-0e99b4307722",
    "metadata": {},
    "outputs": [
     {
@@ -3451,15 +4850,17 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Profession</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Candidate score</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ID</th>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -3470,101 +4871,199 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Managers/executives</td>\n",
-       "      <td>15</td>\n",
-       "      <td>35</td>\n",
-       "      <td>15</td>\n",
-       "      <td>30</td>\n",
-       "      <td>5</td>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>65.136</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Entrepreneurship</td>\n",
-       "      <td>30</td>\n",
-       "      <td>30</td>\n",
-       "      <td>5</td>\n",
-       "      <td>5</td>\n",
-       "      <td>30</td>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>58.710</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Social/Non profit making professions</td>\n",
-       "      <td>5</td>\n",
-       "      <td>5</td>\n",
-       "      <td>35</td>\n",
-       "      <td>35</td>\n",
-       "      <td>20</td>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>56.649</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>54.818</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>46.581</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>Public sector professions</td>\n",
-       "      <td>15</td>\n",
-       "      <td>50</td>\n",
-       "      <td>15</td>\n",
-       "      <td>15</td>\n",
-       "      <td>5</td>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>45.717</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>45.532</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>44.069</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>41.800</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>Scientists/researchers, and engineers</td>\n",
-       "      <td>50</td>\n",
-       "      <td>15</td>\n",
-       "      <td>5</td>\n",
-       "      <td>15</td>\n",
-       "      <td>15</td>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>37.450</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Profession  Openness  Conscientiousness  \\\n",
-       "ID                                                                       \n",
-       "1                     Managers/executives        15                 35   \n",
-       "2                        Entrepreneurship        30                 30   \n",
-       "3    Social/Non profit making professions         5                  5   \n",
-       "4               Public sector professions        15                 50   \n",
-       "5   Scientists/researchers, and engineers        50                 15   \n",
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
        "\n",
-       "    Extraversion  Agreeableness  Non-Neuroticism  \n",
-       "ID                                                \n",
-       "1             15             30                5  \n",
-       "2              5              5               30  \n",
-       "3             35             35               20  \n",
-       "4             15             15                5  \n",
-       "5              5             15               15  "
+       "           Candidate score  \n",
+       "Person ID                   \n",
+       "2                   65.136  \n",
+       "10                  58.710  \n",
+       "6                   56.649  \n",
+       "1                   54.818  \n",
+       "8                   46.581  \n",
+       "4                   45.717  \n",
+       "7                   45.532  \n",
+       "9                   44.069  \n",
+       "3                   41.800  \n",
+       "5                   37.450  "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# Загрузка датафрейма с весовыми коэффициентами\n",
-    "url = 'https://download.sberdisk.ru/download/file/478675798?token=fF5fNZVpthQlEV0&filename=traits_priority_for_professions.csv'\n",
-    "traits_priority_for_professions = pd.read_csv(url)\n",
+    "weights = traits_priority_for_professions.iloc[0].values[1:]\n",
+    "weights = list(map(int, weights))\n",
     "\n",
-    "traits_priority_for_professions.index.name = 'ID'\n",
-    "traits_priority_for_professions.index += 1\n",
-    "traits_priority_for_professions.index = traits_priority_for_professions.index.map(str)\n",
+    "_b5._candidate_ranking(\n",
+    "    weigths_openness = weights[0], \n",
+    "    weigths_conscientiousness = weights[1],\n",
+    "    weigths_extraversion = weights[2],\n",
+    "    weigths_agreeableness = weights[3], \n",
+    "    weigths_non_neuroticism = weights[4],\n",
+    "    out = False\n",
+    ")\n",
     "\n",
-    "traits_priority_for_professions"
+    "_b5._save_logs(df = _b5.df_files_ranking_, name = 'executive_candidate_ranking_mupta_en', out = True)\n",
+    "\n",
+    "# Опционно\n",
+    "df = _b5.df_files_ranking_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "ece309a9-5818-435d-8721-b15e2eca8e01",
+   "id": "b217246c-1cfd-4470-a4df-b335d6f2241e",
    "metadata": {},
    "source": [
-    "#### Ранжирование кандидатов на должность инженера-проектировщика"
+    "<hr>\n",
+    "\n",
+    "Для ранжирования кандидатов по профессиональным навыкам необходимо задать по два коэффициента корреляции для каждого персонального качества личности человека и навыка, а также порога полярности качеств. Эти коэффициенты должны показывать, как измениться оценка качества человека если она больше или меньше заданного порога полярности качеств. \n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между двумя людьми в четырьмя профессиональными навыками, представленных в статье:\n",
+    "\n",
+    "1) Wehner C., de Grip A., Pfeifer H. Do recruiters select workers with different personality traits for different tasks? A discrete choice experiment // Labour Economics. - 2022. - vol. 78. - pp. 102186.\n",
+    "\n",
+    "Представлены 4 профессиональных навыка: \n",
+    "\n",
+    "1) Analytical (Аналитические навыки). Умение эффективно решать новые задачи, требующие глубокого анализа. \n",
+    "2) Interactive (Навыки межличностного общения). Умение убеждать и достигать компромиссов с заказчиками и коллегами.\n",
+    "4) Routine (Способность выполнять рутинную работу). Умение эффективно управлять рутинными задачами, соблюдая точность и внимание к деталям.\n",
+    "5) Non-Routine (Способность выполнять нестандартную работу). Умение реагировать и решать проблемы, не имеющие установленного порядка, проявляя адаптивность и креативные навыки в решении задач.\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции и ранжировать кандидатов по другим профессиональным навыкам."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2b7fc489-957d-4a6f-af41-e9ba012c1e9d",
+   "metadata": {},
+   "source": [
+    "#### Ранжирование кандидатов по профессиональным навыкам"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "id": "6d095685-fda4-4943-9a0f-d0463a39798c",
+   "execution_count": 25,
+   "id": "2424f29a-3270-4b98-b173-51314c769e2e",
    "metadata": {},
    "outputs": [
     {
@@ -3588,17 +5087,15 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>OPE</th>\n",
-       "      <th>CON</th>\n",
-       "      <th>EXT</th>\n",
-       "      <th>AGR</th>\n",
-       "      <th>NNEU</th>\n",
-       "      <th>Candidate score</th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>Score_level</th>\n",
+       "      <th>Analytical</th>\n",
+       "      <th>Interactive</th>\n",
+       "      <th>Routine</th>\n",
+       "      <th>Non-Routine</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
-       "      <th></th>\n",
+       "      <th>ID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -3609,176 +5106,148 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Openness</td>\n",
+       "      <td>high</td>\n",
+       "      <td>0.082</td>\n",
+       "      <td>0.348</td>\n",
+       "      <td>0.571</td>\n",
+       "      <td>0.510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>64.500</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>low</td>\n",
+       "      <td>0.196</td>\n",
+       "      <td>0.152</td>\n",
+       "      <td>0.148</td>\n",
+       "      <td>0.218</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>55.229</td>\n",
+       "      <th>3</th>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>high</td>\n",
+       "      <td>0.994</td>\n",
+       "      <td>1.333</td>\n",
+       "      <td>1.507</td>\n",
+       "      <td>1.258</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
-       "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>55.136</td>\n",
+       "      <th>4</th>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>low</td>\n",
+       "      <td>0.241</td>\n",
+       "      <td>0.188</td>\n",
+       "      <td>0.191</td>\n",
+       "      <td>0.267</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>54.757</td>\n",
+       "      <th>5</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>high</td>\n",
+       "      <td>0.169</td>\n",
+       "      <td>-0.060</td>\n",
+       "      <td>0.258</td>\n",
+       "      <td>0.017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>48.353</td>\n",
+       "      <th>6</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>low</td>\n",
+       "      <td>0.181</td>\n",
+       "      <td>0.135</td>\n",
+       "      <td>0.130</td>\n",
+       "      <td>0.194</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>47.495</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>high</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>0.964</td>\n",
+       "      <td>1.400</td>\n",
+       "      <td>1.191</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
-       "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
-       "      <td>0.434</td>\n",
-       "      <td>46.687</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>42.849</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>low</td>\n",
+       "      <td>0.226</td>\n",
+       "      <td>0.180</td>\n",
+       "      <td>0.189</td>\n",
+       "      <td>0.259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>42.470</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>high</td>\n",
+       "      <td>0.636</td>\n",
+       "      <td>0.777</td>\n",
+       "      <td>0.876</td>\n",
+       "      <td>0.729</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>38.232</td>\n",
+       "      <th>10</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>low</td>\n",
+       "      <td>0.207</td>\n",
+       "      <td>0.159</td>\n",
+       "      <td>0.166</td>\n",
+       "      <td>0.238</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
-       "Person ID                                                                \n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621   \n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499   \n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554   \n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489   \n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444   \n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441   \n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434   \n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397   \n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415   \n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355   \n",
+       "                Trait Score_level  Analytical  Interactive  Routine  \\\n",
+       "ID                                                                    \n",
+       "1            Openness        high       0.082        0.348    0.571   \n",
+       "2            Openness         low       0.196        0.152    0.148   \n",
+       "3   Conscientiousness        high       0.994        1.333    1.507   \n",
+       "4   Conscientiousness         low       0.241        0.188    0.191   \n",
+       "5        Extraversion        high       0.169       -0.060    0.258   \n",
+       "6        Extraversion         low       0.181        0.135    0.130   \n",
+       "7       Agreeableness        high       1.239        0.964    1.400   \n",
+       "8       Agreeableness         low       0.226        0.180    0.189   \n",
+       "9     Non-Neuroticism        high       0.636        0.777    0.876   \n",
+       "10    Non-Neuroticism         low       0.207        0.159    0.166   \n",
        "\n",
-       "           Candidate score  \n",
-       "Person ID                   \n",
-       "2                   64.500  \n",
-       "6                   55.229  \n",
-       "10                  55.136  \n",
-       "1                   54.757  \n",
-       "4                   48.353  \n",
-       "7                   47.495  \n",
-       "8                   46.687  \n",
-       "3                   42.849  \n",
-       "9                   42.470  \n",
-       "5                   38.232  "
+       "    Non-Routine  \n",
+       "ID               \n",
+       "1         0.510  \n",
+       "2         0.218  \n",
+       "3         1.258  \n",
+       "4         0.267  \n",
+       "5         0.017  \n",
+       "6         0.194  \n",
+       "7         1.191  \n",
+       "8         0.259  \n",
+       "9         0.729  \n",
+       "10        0.238  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "weights = traits_priority_for_professions.iloc[4].values[1:]\n",
-    "weights = list(map(int, weights))\n",
-    "\n",
-    "_b5._candidate_ranking(\n",
-    "    weigths_openness = weights[0], \n",
-    "    weigths_conscientiousness = weights[1],\n",
-    "    weigths_extraversion = weights[2],\n",
-    "    weigths_agreeableness = weights[3], \n",
-    "    weigths_non_neuroticism = weights[4],\n",
-    "    out = False\n",
-    ")\n",
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/478678231?token=0qiZwliLtHWWYMv&filename=professional_skills.csv'\n",
+    "df_professional_skills = pd.read_csv(url)\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_ranking_, name = 'engineer_candidate_ranking_mupta_en', out = True)\n",
+    "df_professional_skills.index.name = 'ID'\n",
+    "df_professional_skills.index += 1\n",
+    "df_professional_skills.index = df_professional_skills.index.map(str)\n",
     "\n",
-    "# Опционно\n",
-    "df = _b5.df_files_ranking_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
-    "columns_to_round = df.columns[1:]\n",
-    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d56b0166-8fe2-4995-87d7-97b123176e0c",
-   "metadata": {},
-   "source": [
-    "#### Ранжирование кандидатов на должность менеджера"
+    "df_professional_skills"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "id": "5f54009f-1bc5-49cf-8f33-0e99b4307722",
+   "execution_count": 26,
+   "id": "80a54d9a-6f3c-400b-8cdd-d4ddcde2afc2",
    "metadata": {},
    "outputs": [
     {
@@ -3808,7 +5277,10 @@
        "      <th>EXT</th>\n",
        "      <th>AGR</th>\n",
        "      <th>NNEU</th>\n",
-       "      <th>Candidate score</th>\n",
+       "      <th>Analytical</th>\n",
+       "      <th>Interactive</th>\n",
+       "      <th>Routine</th>\n",
+       "      <th>Non-Routine</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Person ID</th>\n",
@@ -3819,108 +5291,141 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>64.524</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>0.407</td>\n",
+       "      <td>0.443</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.487</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
-       "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>57.218</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>0.376</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>0.542</td>\n",
+       "      <td>0.466</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>55.036</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>0.354</td>\n",
+       "      <td>0.382</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>0.422</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>54.170</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.345</td>\n",
+       "      <td>0.392</td>\n",
+       "      <td>0.499</td>\n",
+       "      <td>0.430</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>47.849</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>0.170</td>\n",
+       "      <td>0.188</td>\n",
+       "      <td>0.206</td>\n",
+       "      <td>0.205</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
-       "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
        "      <td>0.434</td>\n",
-       "      <td>45.344</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>0.167</td>\n",
+       "      <td>0.187</td>\n",
+       "      <td>0.206</td>\n",
+       "      <td>0.203</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>45.284</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>43.064</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.166</td>\n",
+       "      <td>0.218</td>\n",
+       "      <td>0.260</td>\n",
+       "      <td>0.244</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>42.727</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>0.085</td>\n",
+       "      <td>0.066</td>\n",
+       "      <td>0.067</td>\n",
+       "      <td>0.096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.084</td>\n",
+       "      <td>0.094</td>\n",
+       "      <td>0.118</td>\n",
+       "      <td>0.137</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>37.378</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>0.079</td>\n",
+       "      <td>0.061</td>\n",
+       "      <td>0.062</td>\n",
+       "      <td>0.088</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -3929,53 +5434,47 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621   \n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554   \n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499   \n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489   \n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444   \n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434   \n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441   \n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415   \n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397   \n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
        "\n",
-       "           Candidate score  \n",
-       "Person ID                   \n",
-       "2                   64.524  \n",
-       "10                  57.218  \n",
-       "6                   55.036  \n",
-       "1                   54.170  \n",
-       "4                   47.849  \n",
-       "8                   45.344  \n",
-       "7                   45.284  \n",
-       "9                   43.064  \n",
-       "3                   42.727  \n",
-       "5                   37.378  "
+       "           Analytical  Interactive  Routine  Non-Routine  \n",
+       "Person ID                                                 \n",
+       "2               0.407        0.443    0.603        0.487  \n",
+       "10              0.376        0.431    0.542        0.466  \n",
+       "6               0.354        0.382    0.522        0.422  \n",
+       "1               0.345        0.392    0.499        0.430  \n",
+       "4               0.170        0.188    0.206        0.205  \n",
+       "9               0.167        0.187    0.206        0.203  \n",
+       "8               0.166        0.218    0.260        0.244  \n",
+       "3               0.085        0.066    0.067        0.096  \n",
+       "7               0.084        0.094    0.118        0.137  \n",
+       "5               0.079        0.061    0.062        0.088  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "weights = traits_priority_for_professions.iloc[0].values[1:]\n",
-    "weights = list(map(int, weights))\n",
-    "\n",
-    "_b5._candidate_ranking(\n",
-    "    weigths_openness = weights[0], \n",
-    "    weigths_conscientiousness = weights[1],\n",
-    "    weigths_extraversion = weights[2],\n",
-    "    weigths_agreeableness = weights[3], \n",
-    "    weigths_non_neuroticism = weights[4],\n",
-    "    out = False\n",
+    "_b5._priority_skill_calculation(\n",
+    "    correlation_coefficients = df_professional_skills,\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_ranking_, name = 'executive_candidate_ranking_mupta_en', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_priority_skill_, name = 'skill_candidate_ranking_mupta_en', out = True)\n",
     "\n",
     "# Опционно\n",
-    "df = _b5.df_files_ranking_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "df = _b5.df_files_priority_skill_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
     "columns_to_round = df.columns[1:]\n",
     "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
     "df"
@@ -3983,39 +5482,142 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b217246c-1cfd-4470-a4df-b335d6f2241e",
+   "id": "624ef336",
    "metadata": {},
    "source": [
     "<hr>\n",
     "\n",
-    "Для ранжирования кандидатов по профессиональным навыкам необходимо задать по два коэффициента корреляции для каждого персонального качества личности человека и навыка, а также порога полярности качеств. Эти коэффициенты должны показывать, как измениться оценка качества человека если она больше или меньше заданного порога полярности качеств. \n",
-    "\n",
-    "В качестве примера предлагается использование коэффициентов корреляции между двумя людьми в четырьмя профессиональными навыками, представленных в статье:\n",
-    "\n",
-    "1) Wehner C., de Grip A., Pfeifer H. Do recruiters select workers with different personality traits for different tasks? A discrete choice experiment // Labour Economics. - 2022. - vol. 78. - pp. 102186.\n",
-    "\n",
-    "Представлены 4 профессиональных навыка: \n",
-    "\n",
-    "1) Analytical (Аналитические навыки). Умение эффективно решать новые задачи, требующие глубокого анализа. \n",
-    "2) Interactive (Навыки межличностного общения). Умение убеждать и достигать компромиссов с заказчиками и коллегами.\n",
-    "4) Routine (Способность выполнять рутинную работу). Умение эффективно управлять рутинными задачами, соблюдая точность и внимание к деталям.\n",
-    "5) Non-Routine (Способность выполнять нестандартную работу). Умение реагировать и решать проблемы, не имеющие установленного порядка, проявляя адаптивность и креативные навыки в решении задач.\n",
-    "\n",
-    "Пользователь может установить свои коэффициенты корреляции и ранжировать кандидатов по другим профессиональным навыкам."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2b7fc489-957d-4a6f-af41-e9ba012c1e9d",
-   "metadata": {},
-   "source": [
-    "#### Ранжирование кандидатов по профессиональным навыкам"
+    "Для ранжирования кандидатов по одному из шестнадцати типов личности MBTI необходимо задать матрицу корреляции между персональными качествами личности человека и четырьмя диспозициями MBTI, установить порог полярности качеств и указать целевой тип личности MBTI.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции, представленных в статье [1]. Описание типов личности MBTI и соотвествующие им успешные профессии представлены в статье [2].\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "2) Tieger P.D., Barron B., Tieger K. Do what you are: Discover the perfect career for you through the secrets of personality type // Hachette UK. - 2024.\n",
+    "\n",
+    "##### Типы личности MBTI основаны на четырех измерениях личности:\n",
+    "\n",
+    "<div style=\"text-align: center;\">\n",
+    "  <table style=\"width:100%; margin: 0 auto; font-size: 0.6em;\">\n",
+    "    <tr>\n",
+    "      <th>Описание измерения</th>\n",
+    "      <th>Измерение</th>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Как мы взаимодействуем с миром и куда направляем свою энергию</td>\n",
+    "      <td>(E) Экстраверсия - Интроверсия (I)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Вид информации, которую мы естественным образом замечаем</td>\n",
+    "      <td>(S) Сенсорика - Интуиция (N)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Как мы принимаем решения</td>\n",
+    "      <td>(T) Логика - Чувства (F)</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>Предпочитаем ли мы жить более структурированно (принимая решения) или более спонтанно (принимая информацию)</td>\n",
+    "      <td>(J) Оценка - Восприятие (P)</td>\n",
+    "    </tr>\n",
+    "  </table>\n",
+    "</div>\n",
+    "\n",
+    "##### Типы личности MBTI и соотвествующие им успешные профессии:\n",
+    "\n",
+    "<div style=\"text-align: center;\">\n",
+    "  <table style=\"width: 100%; margin: 0 auto; font-size: 0.6em;\">\n",
+    "    <tr>\n",
+    "      <th>Тип личности</th>\n",
+    "      <th>Описание</th>\n",
+    "      <th>Успешные профессии</th>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISTJ</td>\n",
+    "      <td>Этот человек отличается ответственностью, строгостью и педантичностью. Он опирается на объективные факты и склонен к аналитическому мышлению. Приступает к задаче только тогда, когда уверен в своих возможностях и успехе</td>\n",
+    "      <td>Инспектор: бухгалтер, аудитор, бюджетный аналитик, финансовый менеджер, разработчик, системный аналитик, библиотекарь и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISFJ</td>\n",
+    "      <td>Этот человек склонен к самоанализу и анализу окружающих, легко распознает фальшь и предпочитает сохранять психологическую дистанцию. Он исполнителен, внимателен и готов помогать другим. Его силы и энергия исходят из внутренних ресурсов, и он всегда полагается на собственный опыт</td>\n",
+    "      <td>Защитник: медсестра, врач, ветеринар или ветеринарный ассистент, социальный работник, сельскохозяйственный или пищевой ученый, секретарь, водитель и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INFJ</td>\n",
+    "      <td>О таких людях говорят: «ему можно доверять». Он отличается высокой чувствительностью, уделяет большое внимание межличностным отношениям, умеет давать ценные советы и помогает раскрывать потенциал других. Развитая интуиция не только генерирует множество идей, но и способствует самоорганизации</td>\n",
+    "      <td>Советник: психолог, специалист по управлению персоналом, офис-менеджер, специалист по обучению, графический дизайнер и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INTJ</td>\n",
+    "      <td>Этот человек умеет выделять главное, говорит четко и по существу, придерживается практического подхода. Он стремится постоянно улучшать свою работу и всегда ищет способы сделать задачу еще лучше. Пустые разговоры ему не по душе, поэтому он избегает больших шумных компаний и с трудом заводит новые знакомства</td>\n",
+    "      <td>Мастермайнд: аниматор, архитектор, копирайтер, фотограф, тележурналист, видеомонтажер, специалист по бизнес-развитию, исполнительный директор, профессор и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISTP</td>\n",
+    "      <td>Этот человек воспринимает мир через ощущения. По природе эмпат, но чаще сосредоточен на себе. Его умение объективно принимать решения и анализировать ситуацию указывает на технический склад ума. Он всегда соблюдает дедлайны, хотя иногда может поступить неожиданно</td>\n",
+    "      <td>Создатель: инженер, техник, строитель, инспектор, судебный эксперт, программист, разработчик ПО и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ISFP</td>\n",
+    "      <td>Этот человек умеет находить радость в однообразии и рутинных делах. Прекрасно ладит с людьми, избегая конфликтов. Ему важно чувствовать свою значимость и оказывать помощь. Такой человек не стремится руководить или менять других, уважает их личные границы и ожидает того же в ответ. По натуре он приземленный практик, на которого всегда можно положиться</td>\n",
+    "      <td>Композитор: помощник по маркетингу, танцор, шеф-повар, офис-администратор, художник, дизайнер интерьеров, секретарь, медсестра и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INFP</td>\n",
+    "      <td>Этот человек - чувствительный лирик, прекрасно разбирающийся в людях и легко вызывающий у них симпатию. Он обладает отличным чувством юмора и уделяет большое внимание своему внешнему виду. Стремится к самопознанию, гармонии с собой и старается быть полезным окружающим</td>\n",
+    "      <td>Целитель: писатель, дизайнер мультимедиа, менеджер по работе с клиентами, учитель для детей с особыми потребностями, тренер, редактор, модельер и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>INTP</td>\n",
+    "      <td>Этот человек - эрудит с философским складом ума. Он тщательно анализирует свои решения, стремясь к объективности и беспристрастности. Бурные проявления эмоций ему не свойственны. Однако большое количество данных и их изменчивость могут вызывать у него внутреннее напряжение</td>\n",
+    "      <td>Архитектор: технический писатель, веб-разработчик, аналитик информационной безопасности, исследователь, ученый, юрист и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESTP</td>\n",
+    "      <td>Этот человек всегда добивается успеха, невзирая на препятствия, которые лишь усиливают его целеустремленность. Он стремится к лидерским позициям и плохо переносит роль подчиненного. Обычно разрабатывает четкий план действий и неуклонно ему следует</td>\n",
+    "      <td>Промоутер: специалист по работе с клиентами, актер, личный тренер, бренд-амбассадор, менеджер, предприниматель, креативный директор, полицейский, маркетолог, производитель и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESFP</td>\n",
+    "      <td>Этот человек легко выявляет слабые стороны людей, что позволяет ему эффективно манипулировать и управлять. В общении он чаще всего руководствуется собственными интересами и предпочитает жить в настоящем. Часто не завершает начатое, стремясь к быстрым результатам. Однако при этом стремится поддерживать гармоничные отношения с окружающими</td>\n",
+    "      <td>Исполнитель: бортпроводник, артист, учитель, менеджер по связям с общественностью, торговый представитель, организатор мероприятий и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ENFP</td>\n",
+    "      <td>Этот человек - творческая личность и фантазер, обладающий качествами, которые помогают ему успешно взаимодействовать с другими, быть открытым и общительным. Он активно участвует в различных мероприятиях, легко решает возникающие вопросы и демонстрирует гибкость</td>\n",
+    "      <td>Чемпион: медицинский работник, продюсер, продавец-консультант, специалист по обслуживанию клиентов, сценарист, ведущий на ТВ/радио и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ENTP</td>\n",
+    "      <td>Этот человек - изобретательный, инициативный и гибкий. Он генератор идей и первопроходец, который не выносит рутины. Постоянное движение и интуитивное принятие решений всегда сопровождают его в работе</td>\n",
+    "      <td>Новатор: инженер, маркетолог, менеджер по социальным сетям, аналитик управления, руководитель цифрового маркетинга, бизнес-консультант, разработчик игр, менеджер по продажам и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESTJ</td>\n",
+    "      <td>Это трудолюбивый человек, который воспринимает мир таким, какой он есть. Он склонен тщательно планировать и доводить дела до конца. Заботится о своем ближайшем окружении, проявляет добродушие, но иногда может быть вспыльчивым, резким и упрямым</td>\n",
+    "      <td>Супервайзер: управляющий директор, менеджер отеля, финансовый сотрудник, судья, агент по недвижимости, генеральный директор, шеф-повар, менеджер по бизнес-развитию, телемаркетолог и т. д.</td>\n",
+    "    </tr>\n",
+    "    <tr>\n",
+    "      <td>ESFJ</td>\n",
+    "      <td>Этот человек умеет оказывать влияние на людей, проявляет заботу и готов жертвовать собой ради других. Он легко устанавливает контакт с любым человеком и способен направить ситуацию в нужное ему русло</td>\n",
+    "      <td>Поставщик: специалист по технической поддержке, менеджер по работе с клиентами, профессор колледжа, медицинский исследователь, бухгалтер, фотожурналист и т. д.</td>\n",
+    "    </tr>\n",
+    "    <td>ENFJ</td>\n",
+    "      <td>Этот человек отличается эмоциональностью и эмпатией. Его мимика выразительна, а речь — красноречива. Благодаря своей самоорганизованности, он успешно воплощает свои фантазии и идеи в жизнь. Он интуитивно понимает, какое решение следует принять в каждой конкретной ситуации</td>\n",
+    "      <td>Учитель: менеджер по связям с общественностью, менеджер по продажам, директор по управлению персоналом, арт-директор, консультант и т. д.</td>\n",
+    "    </tr>\n",
+    "    <td>ENTJ</td>\n",
+    "      <td>Этот человек легко увлекается, готов рисковать и полагается на интуицию. Без страха внедряет новые технологии и способен глубоко анализировать как себя, так и окружающий мир. Жизнь для него - это борьба, в которой он чувствует себя уверенно. Открыт для новых возможностей, но при этом нуждается в контроле</td>\n",
+    "      <td>Командир: руководитель строительства, администратор службы здравоохранения, финансовый бухгалтер, аудитор, юрист, директор школы, химический инженер, менеджер баз данных и т. д.</td>\n",
+    "    </tr>\n",
+    "  </table>\n",
+    "</div>\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции и ранжировать кандидатов по другим типам личности."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "id": "2424f29a-3270-4b98-b173-51314c769e2e",
+   "execution_count": 27,
+   "id": "fd23c41d",
    "metadata": {},
    "outputs": [
     {
@@ -4040,11 +5642,10 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Trait</th>\n",
-       "      <th>Score_level</th>\n",
-       "      <th>Analytical</th>\n",
-       "      <th>Interactive</th>\n",
-       "      <th>Routine</th>\n",
-       "      <th>Non-Routine</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ID</th>\n",
@@ -4053,153 +5654,84 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Openness</td>\n",
-       "      <td>high</td>\n",
-       "      <td>0.082</td>\n",
-       "      <td>0.348</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.510</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.14</td>\n",
+       "      <td>-0.16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>Openness</td>\n",
-       "      <td>low</td>\n",
-       "      <td>0.196</td>\n",
-       "      <td>0.152</td>\n",
-       "      <td>0.148</td>\n",
-       "      <td>0.218</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>high</td>\n",
-       "      <td>0.994</td>\n",
-       "      <td>1.333</td>\n",
-       "      <td>1.507</td>\n",
-       "      <td>1.258</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>low</td>\n",
-       "      <td>0.241</td>\n",
-       "      <td>0.188</td>\n",
-       "      <td>0.191</td>\n",
-       "      <td>0.267</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>Extraversion</td>\n",
-       "      <td>high</td>\n",
-       "      <td>0.169</td>\n",
-       "      <td>-0.060</td>\n",
-       "      <td>0.258</td>\n",
-       "      <td>0.017</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>-0.04</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
+       "      <th>3</th>\n",
        "      <td>Extraversion</td>\n",
-       "      <td>low</td>\n",
-       "      <td>0.181</td>\n",
-       "      <td>0.135</td>\n",
-       "      <td>0.130</td>\n",
-       "      <td>0.194</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>high</td>\n",
-       "      <td>1.239</td>\n",
-       "      <td>0.964</td>\n",
-       "      <td>1.400</td>\n",
-       "      <td>1.191</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.07</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
+       "      <th>4</th>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>low</td>\n",
-       "      <td>0.226</td>\n",
-       "      <td>0.180</td>\n",
-       "      <td>0.189</td>\n",
-       "      <td>0.259</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>Non-Neuroticism</td>\n",
-       "      <td>high</td>\n",
-       "      <td>0.636</td>\n",
-       "      <td>0.777</td>\n",
-       "      <td>0.876</td>\n",
-       "      <td>0.729</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>-0.35</td>\n",
+       "      <td>0.03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
+       "      <th>5</th>\n",
        "      <td>Non-Neuroticism</td>\n",
-       "      <td>low</td>\n",
-       "      <td>0.207</td>\n",
-       "      <td>0.159</td>\n",
-       "      <td>0.166</td>\n",
-       "      <td>0.238</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Trait Score_level  Analytical  Interactive  Routine  \\\n",
-       "ID                                                                    \n",
-       "1            Openness        high       0.082        0.348    0.571   \n",
-       "2            Openness         low       0.196        0.152    0.148   \n",
-       "3   Conscientiousness        high       0.994        1.333    1.507   \n",
-       "4   Conscientiousness         low       0.241        0.188    0.191   \n",
-       "5        Extraversion        high       0.169       -0.060    0.258   \n",
-       "6        Extraversion         low       0.181        0.135    0.130   \n",
-       "7       Agreeableness        high       1.239        0.964    1.400   \n",
-       "8       Agreeableness         low       0.226        0.180    0.189   \n",
-       "9     Non-Neuroticism        high       0.636        0.777    0.876   \n",
-       "10    Non-Neuroticism         low       0.207        0.159    0.166   \n",
-       "\n",
-       "    Non-Routine  \n",
-       "ID               \n",
-       "1         0.510  \n",
-       "2         0.218  \n",
-       "3         1.258  \n",
-       "4         0.267  \n",
-       "5         0.017  \n",
-       "6         0.194  \n",
-       "7         1.191  \n",
-       "8         0.259  \n",
-       "9         0.729  \n",
-       "10        0.238  "
+       "                Trait    EI    SN    TF    JP\n",
+       "ID                                           \n",
+       "1            Openness  0.09 -0.03 -0.14 -0.16\n",
+       "2   Conscientiousness  0.04 -0.04  0.20  0.14\n",
+       "3        Extraversion  0.20 -0.03  0.01 -0.07\n",
+       "4       Agreeableness  0.02  0.05 -0.35  0.03\n",
+       "5     Non-Neuroticism  0.08  0.00  0.16  0.00"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Загрузка датафрейма с коэффициентами корреляции\n",
-    "url = 'https://download.sberdisk.ru/download/file/478678231?token=0qiZwliLtHWWYMv&filename=professional_skills.csv'\n",
-    "df_professional_skills = pd.read_csv(url)\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
     "\n",
-    "df_professional_skills.index.name = 'ID'\n",
-    "df_professional_skills.index += 1\n",
-    "df_professional_skills.index = df_professional_skills.index.map(str)\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
     "\n",
-    "df_professional_skills"
+    "df_correlation_coefficients"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "id": "80a54d9a-6f3c-400b-8cdd-d4ddcde2afc2",
+   "execution_count": 30,
+   "id": "69eb410d",
    "metadata": {},
    "outputs": [
     {
@@ -4229,10 +5761,13 @@
        "      <th>EXT</th>\n",
        "      <th>AGR</th>\n",
        "      <th>NNEU</th>\n",
-       "      <th>Analytical</th>\n",
-       "      <th>Interactive</th>\n",
-       "      <th>Routine</th>\n",
-       "      <th>Non-Routine</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>MBTI_Score</th>\n",
+       "      <th>Match</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Person ID</th>\n",
@@ -4246,138 +5781,171 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>0.402</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.479</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
        "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>0.365</td>\n",
-       "      <td>0.419</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.451</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>0.271478</td>\n",
+       "      <td>-0.032624</td>\n",
+       "      <td>-0.074766</td>\n",
+       "      <td>-0.034321</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.284152</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>0.229601</td>\n",
+       "      <td>-0.024972</td>\n",
+       "      <td>-0.091174</td>\n",
+       "      <td>-0.031648</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.259311</td>\n",
+       "      <td>75.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
        "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.301</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.422</td>\n",
-       "      <td>0.377</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>0.048690</td>\n",
+       "      <td>-0.000776</td>\n",
+       "      <td>-0.066064</td>\n",
+       "      <td>0.049778</td>\n",
+       "      <td>ENFJ</td>\n",
+       "      <td>0.165309</td>\n",
+       "      <td>100.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>0.299</td>\n",
-       "      <td>0.325</td>\n",
-       "      <td>0.421</td>\n",
-       "      <td>0.375</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.040210</td>\n",
+       "      <td>0.003122</td>\n",
+       "      <td>-0.103169</td>\n",
+       "      <td>0.029258</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>0.129477</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>0.176</td>\n",
-       "      <td>0.194</td>\n",
-       "      <td>0.212</td>\n",
-       "      <td>0.212</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
-       "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
-       "      <td>0.434</td>\n",
-       "      <td>0.172</td>\n",
-       "      <td>0.192</td>\n",
-       "      <td>0.210</td>\n",
-       "      <td>0.208</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>-0.140376</td>\n",
+       "      <td>-0.016646</td>\n",
+       "      <td>0.250115</td>\n",
+       "      <td>0.159620</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>0.088133</td>\n",
+       "      <td>50.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.088</td>\n",
-       "      <td>0.068</td>\n",
-       "      <td>0.069</td>\n",
-       "      <td>0.099</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>0.087</td>\n",
-       "      <td>0.068</td>\n",
-       "      <td>0.069</td>\n",
-       "      <td>0.098</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>-0.122322</td>\n",
+       "      <td>-0.020306</td>\n",
+       "      <td>0.240365</td>\n",
+       "      <td>0.148065</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>0.084185</td>\n",
+       "      <td>50.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>-0.101987</td>\n",
+       "      <td>-0.007200</td>\n",
+       "      <td>-0.078923</td>\n",
+       "      <td>-0.128220</td>\n",
+       "      <td>INFP</td>\n",
+       "      <td>0.043061</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>0.084</td>\n",
-       "      <td>0.094</td>\n",
-       "      <td>0.118</td>\n",
-       "      <td>0.136</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>-0.040020</td>\n",
+       "      <td>-0.049474</td>\n",
+       "      <td>0.117143</td>\n",
+       "      <td>0.004070</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>0.026772</td>\n",
+       "      <td>50.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>0.078</td>\n",
-       "      <td>0.060</td>\n",
-       "      <td>0.061</td>\n",
-       "      <td>0.087</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>-0.152724</td>\n",
+       "      <td>0.014281</td>\n",
+       "      <td>0.070700</td>\n",
+       "      <td>0.025861</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>0.006465</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>-0.155235</td>\n",
+       "      <td>0.019207</td>\n",
+       "      <td>0.050250</td>\n",
+       "      <td>0.012514</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>0.003128</td>\n",
+       "      <td>25.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -4386,48 +5954,49 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621   \n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554   \n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499   \n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489   \n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444   \n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434   \n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415   \n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397   \n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441   \n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
        "\n",
-       "           Analytical  Interactive  Routine  Non-Routine  \n",
-       "Person ID                                                 \n",
-       "2               0.402        0.436    0.595        0.479  \n",
-       "10              0.365        0.419    0.524        0.451  \n",
-       "6               0.301        0.327    0.422        0.377  \n",
-       "1               0.299        0.325    0.421        0.375  \n",
-       "4               0.176        0.194    0.212        0.212  \n",
-       "8               0.172        0.192    0.210        0.208  \n",
-       "9               0.088        0.068    0.069        0.099  \n",
-       "3               0.087        0.068    0.069        0.098  \n",
-       "7               0.084        0.094    0.118        0.136  \n",
-       "5               0.078        0.060    0.061        0.087  "
+       "                 EI        SN        TF        JP  MBTI  MBTI_Score  Match  \n",
+       "Person ID                                                                   \n",
+       "2          0.271478 -0.032624 -0.074766 -0.034321  ENFP    0.284152   75.0  \n",
+       "6          0.229601 -0.024972 -0.091174 -0.031648  ENFP    0.259311   75.0  \n",
+       "10         0.048690 -0.000776 -0.066064  0.049778  ENFJ    0.165309  100.0  \n",
+       "1          0.040210  0.003122 -0.103169  0.029258  ESFJ    0.129477   75.0  \n",
+       "4         -0.140376 -0.016646  0.250115  0.159620  INTJ    0.088133   50.0  \n",
+       "9         -0.122322 -0.020306  0.240365  0.148065  INTJ    0.084185   50.0  \n",
+       "7         -0.101987 -0.007200 -0.078923 -0.128220  INFP    0.043061   50.0  \n",
+       "8         -0.040020 -0.049474  0.117143  0.004070  INTJ    0.026772   50.0  \n",
+       "5         -0.152724  0.014281  0.070700  0.025861  ISTJ    0.006465   25.0  \n",
+       "3         -0.155235  0.019207  0.050250  0.012514  ISTJ    0.003128   25.0  "
       ]
      },
-     "execution_count": 20,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "_b5._priority_skill_calculation(\n",
-    "    correlation_coefficients = df_professional_skills,\n",
+    "_b5._professional_match(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    personality_type = \"ENFJ\",\n",
     "    threshold = 0.5,\n",
     "    out = True\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_priority_skill_, name = 'skill_candidate_ranking_mupta_en', out = True)\n",
+    "_b5._save_logs(df = _b5._df_files_MBTI_job_match, name = 'MBTI_ranking_mupta_en', out = True)\n",
     "\n",
     "# Опционно\n",
-    "df = _b5.df_files_priority_skill_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
-    "columns_to_round = df.columns[1:]\n",
+    "df = _b5.df_files_MBTI_job_match_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
     "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
     "df"
    ]
@@ -4449,7 +6018,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.11"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/user_guide/notebooks/Pipeline_practical_task_2.ipynb b/docs/source/user_guide/notebooks/Pipeline_practical_task_2.ipynb
index 7668848..c4930bd 100644
--- a/docs/source/user_guide/notebooks/Pipeline_practical_task_2.ipynb
+++ b/docs/source/user_guide/notebooks/Pipeline_practical_task_2.ipynb
@@ -60,7 +60,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:05:15</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:10:50</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -72,7 +72,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:05:17</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_FI\\test\\_plk5k7PBEg.003.mp4 ...</span></p>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:10:50</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_FI\\test\\_plk5k7PBEg.003.mp4 ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -123,92 +123,92 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581159</td>\n",
-       "      <td>0.628822</td>\n",
-       "      <td>0.466609</td>\n",
-       "      <td>0.622129</td>\n",
-       "      <td>0.553832</td>\n",
+       "      <td>0.618917</td>\n",
+       "      <td>0.660694</td>\n",
+       "      <td>0.477656</td>\n",
+       "      <td>0.654437</td>\n",
+       "      <td>0.601256</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.463991</td>\n",
-       "      <td>0.418851</td>\n",
-       "      <td>0.41301</td>\n",
-       "      <td>0.493329</td>\n",
-       "      <td>0.423093</td>\n",
+       "      <td>0.461732</td>\n",
+       "      <td>0.413451</td>\n",
+       "      <td>0.415706</td>\n",
+       "      <td>0.498301</td>\n",
+       "      <td>0.431224</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
-       "      <td>0.454281</td>\n",
-       "      <td>0.415049</td>\n",
-       "      <td>0.39189</td>\n",
-       "      <td>0.485114</td>\n",
-       "      <td>0.420741</td>\n",
+       "      <td>0.468002</td>\n",
+       "      <td>0.448618</td>\n",
+       "      <td>0.371742</td>\n",
+       "      <td>0.509602</td>\n",
+       "      <td>0.453739</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588461</td>\n",
-       "      <td>0.643233</td>\n",
-       "      <td>0.530789</td>\n",
-       "      <td>0.603038</td>\n",
-       "      <td>0.593398</td>\n",
+       "      <td>0.585348</td>\n",
+       "      <td>0.616446</td>\n",
+       "      <td>0.49443</td>\n",
+       "      <td>0.605614</td>\n",
+       "      <td>0.587017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633433</td>\n",
-       "      <td>0.533295</td>\n",
-       "      <td>0.523742</td>\n",
-       "      <td>0.608591</td>\n",
-       "      <td>0.588456</td>\n",
+       "      <td>0.680991</td>\n",
+       "      <td>0.56602</td>\n",
+       "      <td>0.553915</td>\n",
+       "      <td>0.646545</td>\n",
+       "      <td>0.64246</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.636944</td>\n",
-       "      <td>0.542386</td>\n",
-       "      <td>0.558461</td>\n",
-       "      <td>0.570975</td>\n",
-       "      <td>0.558983</td>\n",
+       "      <td>0.66342</td>\n",
+       "      <td>0.551018</td>\n",
+       "      <td>0.557912</td>\n",
+       "      <td>0.585238</td>\n",
+       "      <td>0.587174</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
-       "      <td>0.531518</td>\n",
-       "      <td>0.376987</td>\n",
-       "      <td>0.393309</td>\n",
-       "      <td>0.4904</td>\n",
-       "      <td>0.447881</td>\n",
+       "      <td>0.590237</td>\n",
+       "      <td>0.399273</td>\n",
+       "      <td>0.409554</td>\n",
+       "      <td>0.531861</td>\n",
+       "      <td>0.507134</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610342</td>\n",
-       "      <td>0.541418</td>\n",
-       "      <td>0.563163</td>\n",
-       "      <td>0.595013</td>\n",
-       "      <td>0.569461</td>\n",
+       "      <td>0.60577</td>\n",
+       "      <td>0.523617</td>\n",
+       "      <td>0.531137</td>\n",
+       "      <td>0.594406</td>\n",
+       "      <td>0.57984</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.495809</td>\n",
-       "      <td>0.458526</td>\n",
-       "      <td>0.414436</td>\n",
-       "      <td>0.469152</td>\n",
-       "      <td>0.435461</td>\n",
+       "      <td>0.511002</td>\n",
+       "      <td>0.464702</td>\n",
+       "      <td>0.390882</td>\n",
+       "      <td>0.443663</td>\n",
+       "      <td>0.438811</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.60707</td>\n",
-       "      <td>0.591893</td>\n",
-       "      <td>0.520662</td>\n",
-       "      <td>0.603938</td>\n",
-       "      <td>0.565726</td>\n",
+       "      <td>0.647606</td>\n",
+       "      <td>0.610466</td>\n",
+       "      <td>0.524718</td>\n",
+       "      <td>0.61428</td>\n",
+       "      <td>0.606428</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -217,29 +217,29 @@
       "text/plain": [
        "                          Path  Openness Conscientiousness Extraversion  \\\n",
        "Person ID                                                                 \n",
-       "1          2d6btbaNdfo.000.mp4  0.581159          0.628822     0.466609   \n",
-       "2          300gK3CnzW0.001.mp4  0.463991          0.418851      0.41301   \n",
-       "3          300gK3CnzW0.003.mp4  0.454281          0.415049      0.39189   \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588461          0.643233     0.530789   \n",
-       "5          be0DQawtVkE.002.mp4  0.633433          0.533295     0.523742   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.636944          0.542386     0.558461   \n",
-       "7          g24JGYuT74A.004.mp4  0.531518          0.376987     0.393309   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610342          0.541418     0.563163   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.495809          0.458526     0.414436   \n",
-       "10         _plk5k7PBEg.003.mp4   0.60707          0.591893     0.520662   \n",
+       "1          2d6btbaNdfo.000.mp4  0.618917          0.660694     0.477656   \n",
+       "2          300gK3CnzW0.001.mp4  0.461732          0.413451     0.415706   \n",
+       "3          300gK3CnzW0.003.mp4  0.468002          0.448618     0.371742   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585348          0.616446      0.49443   \n",
+       "5          be0DQawtVkE.002.mp4  0.680991           0.56602     0.553915   \n",
+       "6          cLaZxEf1nE4.004.mp4   0.66342          0.551018     0.557912   \n",
+       "7          g24JGYuT74A.004.mp4  0.590237          0.399273     0.409554   \n",
+       "8          JZNMxa3OKHY.000.mp4   0.60577          0.523617     0.531137   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511002          0.464702     0.390882   \n",
+       "10         _plk5k7PBEg.003.mp4  0.647606          0.610466     0.524718   \n",
        "\n",
        "          Agreeableness Non-Neuroticism  \n",
        "Person ID                                \n",
-       "1              0.622129        0.553832  \n",
-       "2              0.493329        0.423093  \n",
-       "3              0.485114        0.420741  \n",
-       "4              0.603038        0.593398  \n",
-       "5              0.608591        0.588456  \n",
-       "6              0.570975        0.558983  \n",
-       "7                0.4904        0.447881  \n",
-       "8              0.595013        0.569461  \n",
-       "9              0.469152        0.435461  \n",
-       "10             0.603938        0.565726  "
+       "1              0.654437        0.601256  \n",
+       "2              0.498301        0.431224  \n",
+       "3              0.509602        0.453739  \n",
+       "4              0.605614        0.587017  \n",
+       "5              0.646545         0.64246  \n",
+       "6              0.585238        0.587174  \n",
+       "7              0.531861        0.507134  \n",
+       "8              0.594406         0.57984  \n",
+       "9              0.443663        0.438811  \n",
+       "10              0.61428        0.606428  "
       ]
      },
      "metadata": {},
@@ -248,7 +248,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:05:17</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:10:50</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -298,21 +298,21 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MAE</th>\n",
-       "      <td>0.0589</td>\n",
-       "      <td>0.0612</td>\n",
-       "      <td>0.0864</td>\n",
-       "      <td>0.0697</td>\n",
-       "      <td>0.0582</td>\n",
-       "      <td>0.0669</td>\n",
+       "      <td>0.0735</td>\n",
+       "      <td>0.0631</td>\n",
+       "      <td>0.0914</td>\n",
+       "      <td>0.0706</td>\n",
+       "      <td>0.0691</td>\n",
+       "      <td>0.0735</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.9411</td>\n",
-       "      <td>0.9388</td>\n",
-       "      <td>0.9136</td>\n",
-       "      <td>0.9303</td>\n",
-       "      <td>0.9418</td>\n",
-       "      <td>0.9331</td>\n",
+       "      <td>0.9265</td>\n",
+       "      <td>0.9369</td>\n",
+       "      <td>0.9086</td>\n",
+       "      <td>0.9294</td>\n",
+       "      <td>0.9309</td>\n",
+       "      <td>0.9265</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -321,13 +321,13 @@
       "text/plain": [
        "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
        "Metrics                                                              \n",
-       "MAE         0.0589             0.0612        0.0864         0.0697   \n",
-       "Accuracy    0.9411             0.9388        0.9136         0.9303   \n",
+       "MAE         0.0735             0.0631        0.0914         0.0706   \n",
+       "Accuracy    0.9265             0.9369        0.9086         0.9294   \n",
        "\n",
        "          Non-Neuroticism    Mean  \n",
        "Metrics                            \n",
-       "MAE                0.0582  0.0669  \n",
-       "Accuracy           0.9418  0.9331  "
+       "MAE                0.0691  0.0735  \n",
+       "Accuracy           0.9309  0.9265  "
       ]
      },
      "metadata": {},
@@ -336,7 +336,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:05:17</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0669</span>, средняя точность: <span style=\"color:#1776D2\">0.9331</span> ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:10:50</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0735</span>, средняя точность: <span style=\"color:#1776D2\">0.9265</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -360,7 +360,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 64.147 сек. ---**</span>"
+       "<span style=\"color:#666\">**--- Время выполнения: 35.449 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -402,11 +402,11 @@
     "res_load_model_nn = _b5.load_audio_model_nn()\n",
     "\n",
     "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование видеомоделей\n",
     "res_load_model_hc = _b5.load_video_model_hc(lang='en')\n",
@@ -414,14 +414,14 @@
     "res_load_model_nn = _b5.load_video_model_nn()\n",
     "\n",
     "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
     "res_load_text_features = _b5.load_text_features()\n",
@@ -433,18 +433,18 @@
     "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
     "\n",
     "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование модели для мультимодального объединения информации\n",
     "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
     "\n",
     "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
     "\n",
     "PATH_TO_DIR = './video_FI/'\n",
     "PATH_SAVE_VIDEO = './video_FI/test/'\n",
@@ -475,7 +475,7 @@
     "_b5.ext_ = ['.mp4'] # Расширения искомых файлов\n",
     "\n",
     "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_[corpus]['sberdisk']\n",
+    "url_accuracy = _b5.true_traits_[corpus]['googledisk']\n",
     "\n",
     "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = 'en')"
    ]
@@ -753,11 +753,11 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
        "      <td>Safe and reliable</td>\n",
        "      <td>Practical and easy to use</td>\n",
        "      <td>Economical/low cost</td>\n",
@@ -768,11 +768,11 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
+       "      <td>0.462</td>\n",
        "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
        "      <td>Classic car features</td>\n",
        "      <td>Fashion and attention</td>\n",
        "      <td>Luxury additions</td>\n",
@@ -783,11 +783,11 @@
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
        "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
        "      <td>Classic car features</td>\n",
        "      <td>Fashion and attention</td>\n",
        "      <td>Luxury additions</td>\n",
@@ -798,11 +798,11 @@
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
        "      <td>Safe and reliable</td>\n",
        "      <td>Practical and easy to use</td>\n",
        "      <td>Economical/low cost</td>\n",
@@ -813,71 +813,71 @@
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>Practical and easy to use</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
        "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
        "      <td>Economical/low cost</td>\n",
        "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "      <td>Openness</td>\n",
-       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
        "      <td>Safe and reliable</td>\n",
-       "      <td>Economical/low cost</td>\n",
        "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Openness</td>\n",
-       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
        "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
+       "      <td>0.507</td>\n",
        "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
+       "      <td>Recreation</td>\n",
        "      <td>Luxury additions</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
-       "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>Practical and easy to use</td>\n",
        "      <td>Safe and reliable</td>\n",
        "      <td>Economical/low cost</td>\n",
-       "      <td>Practical and easy to use</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Openness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
        "      <td>Classic car features</td>\n",
        "      <td>Fashion and attention</td>\n",
        "      <td>Luxury additions</td>\n",
@@ -888,11 +888,11 @@
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.566</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
        "      <td>Safe and reliable</td>\n",
        "      <td>Practical and easy to use</td>\n",
        "      <td>Economical/low cost</td>\n",
@@ -907,16 +907,16 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                           \n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554   \n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423   \n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421   \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593   \n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559   \n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435   \n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606   \n",
        "\n",
        "                          Priority 1                 Priority 2  \\\n",
        "Person ID                                                         \n",
@@ -924,25 +924,25 @@
        "2               Classic car features      Fashion and attention   \n",
        "3               Classic car features      Fashion and attention   \n",
        "4                  Safe and reliable  Practical and easy to use   \n",
-       "5          Practical and easy to use          Safe and reliable   \n",
-       "6                  Safe and reliable        Economical/low cost   \n",
-       "7               Classic car features      Fashion and attention   \n",
-       "8                  Safe and reliable        Economical/low cost   \n",
+       "5                  Safe and reliable  Practical and easy to use   \n",
+       "6                  Safe and reliable  Practical and easy to use   \n",
+       "7               Classic car features                 Recreation   \n",
+       "8          Practical and easy to use          Safe and reliable   \n",
        "9               Classic car features      Fashion and attention   \n",
        "10                 Safe and reliable  Practical and easy to use   \n",
        "\n",
-       "                          Priority 3 Trait importance 1 Trait importance 2  \\\n",
-       "Person ID                                                                    \n",
-       "1                Economical/low cost  Conscientiousness      Agreeableness   \n",
-       "2                   Luxury additions      Agreeableness  Conscientiousness   \n",
-       "3                   Luxury additions      Agreeableness  Conscientiousness   \n",
-       "4                Economical/low cost  Conscientiousness      Agreeableness   \n",
-       "5                Economical/low cost      Agreeableness           Openness   \n",
-       "6          Practical and easy to use      Agreeableness           Openness   \n",
-       "7                   Luxury additions      Agreeableness  Conscientiousness   \n",
-       "8          Practical and easy to use      Agreeableness           Openness   \n",
-       "9                   Luxury additions      Agreeableness  Conscientiousness   \n",
-       "10               Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "                    Priority 3 Trait importance 1 Trait importance 2  \\\n",
+       "Person ID                                                              \n",
+       "1          Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "2             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "3             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "4          Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "5          Economical/low cost      Agreeableness  Conscientiousness   \n",
+       "6          Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "7             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "8          Economical/low cost      Agreeableness           Openness   \n",
+       "9             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "10         Economical/low cost  Conscientiousness      Agreeableness   \n",
        "\n",
        "          Trait importance 3  \n",
        "Person ID                     \n",
@@ -950,10 +950,10 @@
        "2                   Openness  \n",
        "3                   Openness  \n",
        "4                   Openness  \n",
-       "5            Non-Neuroticism  \n",
-       "6               Extraversion  \n",
-       "7                   Openness  \n",
-       "8               Extraversion  \n",
+       "5                   Openness  \n",
+       "6                   Openness  \n",
+       "7            Non-Neuroticism  \n",
+       "8            Non-Neuroticism  \n",
        "9                   Openness  \n",
        "10                  Openness  "
       ]
@@ -1276,11 +1276,11 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
        "      <td>Game Casino</td>\n",
        "      <td>Game Educational</td>\n",
        "      <td>Game Trivia</td>\n",
@@ -1291,11 +1291,11 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
+       "      <td>0.462</td>\n",
        "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
        "      <td>Media and Video</td>\n",
        "      <td>Entertainment</td>\n",
        "      <td>Health and Fitness</td>\n",
@@ -1306,11 +1306,11 @@
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
        "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
        "      <td>Media and Video</td>\n",
        "      <td>Entertainment</td>\n",
        "      <td>Health and Fitness</td>\n",
@@ -1321,11 +1321,11 @@
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
        "      <td>Game Casino</td>\n",
        "      <td>Game Educational</td>\n",
        "      <td>Game Trivia</td>\n",
@@ -1336,86 +1336,86 @@
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
        "      <td>Game Casino</td>\n",
-       "      <td>Game Educational</td>\n",
-       "      <td>Game Simulation</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Trivia</td>\n",
        "      <td>Non-Neuroticism</td>\n",
+       "      <td>Extraversion</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
        "      <td>Game Casino</td>\n",
-       "      <td>Game Simulation</td>\n",
-       "      <td>Game Educational</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Trivia</td>\n",
        "      <td>Non-Neuroticism</td>\n",
-       "      <td>Agreeableness</td>\n",
        "      <td>Extraversion</td>\n",
+       "      <td>Agreeableness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
        "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Media and Video</td>\n",
        "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
+       "      <td>Openness</td>\n",
        "      <td>Conscientiousness</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
-       "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
        "      <td>Game Casino</td>\n",
-       "      <td>Game Simulation</td>\n",
        "      <td>Game Educational</td>\n",
+       "      <td>Game Simulation</td>\n",
        "      <td>Non-Neuroticism</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
        "      <td>Media and Video</td>\n",
        "      <td>Entertainment</td>\n",
        "      <td>Health and Fitness</td>\n",
-       "      <td>Conscientiousness</td>\n",
        "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.566</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
        "      <td>Game Casino</td>\n",
        "      <td>Game Educational</td>\n",
        "      <td>Game Trivia</td>\n",
@@ -1430,29 +1430,29 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                           \n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554   \n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423   \n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421   \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593   \n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559   \n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435   \n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606   \n",
        "\n",
-       "                Priority 1        Priority 2          Priority 3  \\\n",
-       "Person ID                                                          \n",
-       "1              Game Casino  Game Educational         Game Trivia   \n",
-       "2          Media and Video     Entertainment  Health and Fitness   \n",
-       "3          Media and Video     Entertainment  Health and Fitness   \n",
-       "4              Game Casino  Game Educational         Game Trivia   \n",
-       "5              Game Casino  Game Educational     Game Simulation   \n",
-       "6              Game Casino   Game Simulation    Game Educational   \n",
-       "7          Media and Video     Entertainment  Health and Fitness   \n",
-       "8              Game Casino   Game Simulation    Game Educational   \n",
-       "9          Media and Video     Entertainment  Health and Fitness   \n",
-       "10             Game Casino  Game Educational         Game Trivia   \n",
+       "                   Priority 1        Priority 2          Priority 3  \\\n",
+       "Person ID                                                             \n",
+       "1                 Game Casino  Game Educational         Game Trivia   \n",
+       "2             Media and Video     Entertainment  Health and Fitness   \n",
+       "3             Media and Video     Entertainment  Health and Fitness   \n",
+       "4                 Game Casino  Game Educational         Game Trivia   \n",
+       "5                 Game Casino     Communication         Game Trivia   \n",
+       "6                 Game Casino     Communication         Game Trivia   \n",
+       "7          Health and Fitness   Media and Video       Entertainment   \n",
+       "8                 Game Casino  Game Educational     Game Simulation   \n",
+       "9             Media and Video     Entertainment  Health and Fitness   \n",
+       "10                Game Casino  Game Educational         Game Trivia   \n",
        "\n",
        "          Trait importance 1 Trait importance 2 Trait importance 3  \n",
        "Person ID                                                           \n",
@@ -1460,11 +1460,11 @@
        "2          Conscientiousness      Agreeableness       Extraversion  \n",
        "3          Conscientiousness      Agreeableness       Extraversion  \n",
        "4            Non-Neuroticism  Conscientiousness      Agreeableness  \n",
-       "5            Non-Neuroticism      Agreeableness           Openness  \n",
-       "6            Non-Neuroticism      Agreeableness       Extraversion  \n",
-       "7          Conscientiousness      Agreeableness       Extraversion  \n",
-       "8            Non-Neuroticism      Agreeableness       Extraversion  \n",
-       "9          Conscientiousness      Agreeableness       Extraversion  \n",
+       "5            Non-Neuroticism       Extraversion      Agreeableness  \n",
+       "6            Non-Neuroticism       Extraversion      Agreeableness  \n",
+       "7                   Openness  Conscientiousness      Agreeableness  \n",
+       "8            Non-Neuroticism      Agreeableness           Openness  \n",
+       "9              Agreeableness  Conscientiousness       Extraversion  \n",
        "10           Non-Neuroticism      Agreeableness  Conscientiousness  "
       ]
      },
@@ -1494,42 +1494,22 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2297292e-1e4b-44e0-9c85-ab0fba999892",
+   "id": "dca42ad9",
    "metadata": {},
    "source": [
-    "### `MuPTA` (ru)"
+    "#### Прогнозирование потребительских предпочтений по стилю одежды\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и стилем одежды, представленными в статье:\n",
+    "\n",
+    "1) Stolovy T. Styling the self: clothing practices, personality traits, and body image among Israeli women // Frontiers in psychology. - 2022. - vol. 12. - 719318."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "3887d07c-eef2-4980-8d82-cabf6568aa7d",
+   "id": "29e56565",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:13:25</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:13:30</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/html": [
@@ -1551,15 +1531,15 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>Comfort</th>\n",
+       "      <th>Camouflage</th>\n",
+       "      <th>Assurance</th>\n",
+       "      <th>Fashion</th>\n",
+       "      <th>Individuality</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
+       "      <th>ID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -1571,141 +1551,86 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758137</td>\n",
-       "      <td>0.693356</td>\n",
-       "      <td>0.650108</td>\n",
-       "      <td>0.744589</td>\n",
-       "      <td>0.488671</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.24</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.31</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.681602</td>\n",
-       "      <td>0.654339</td>\n",
-       "      <td>0.607156</td>\n",
-       "      <td>0.731282</td>\n",
-       "      <td>0.417908</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.24</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666104</td>\n",
-       "      <td>0.656836</td>\n",
-       "      <td>0.567863</td>\n",
-       "      <td>0.685067</td>\n",
-       "      <td>0.378102</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>-0.01</td>\n",
+       "      <td>-0.19</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694171</td>\n",
-       "      <td>0.596195</td>\n",
-       "      <td>0.571414</td>\n",
-       "      <td>0.66223</td>\n",
-       "      <td>0.348639</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>-0.16</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>-0.09</td>\n",
+       "      <td>-0.05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.712885</td>\n",
-       "      <td>0.594764</td>\n",
-       "      <td>0.571709</td>\n",
-       "      <td>0.716696</td>\n",
-       "      <td>0.37802</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664158</td>\n",
-       "      <td>0.670411</td>\n",
-       "      <td>0.60421</td>\n",
-       "      <td>0.696056</td>\n",
-       "      <td>0.399842</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761213</td>\n",
-       "      <td>0.652635</td>\n",
-       "      <td>0.651028</td>\n",
-       "      <td>0.788677</td>\n",
-       "      <td>0.459676</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.692788</td>\n",
-       "      <td>0.68324</td>\n",
-       "      <td>0.616737</td>\n",
-       "      <td>0.795205</td>\n",
-       "      <td>0.447242</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.705923</td>\n",
-       "      <td>0.658382</td>\n",
-       "      <td>0.610645</td>\n",
-       "      <td>0.697415</td>\n",
-       "      <td>0.411988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753417</td>\n",
-       "      <td>0.708372</td>\n",
-       "      <td>0.654608</td>\n",
-       "      <td>0.816416</td>\n",
-       "      <td>0.504743</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>-0.16</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.06</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path  Openness Conscientiousness Extraversion  \\\n",
-       "Person ID                                                                      \n",
-       "1          speaker_01_center_83.mov  0.758137          0.693356     0.650108   \n",
-       "2          speaker_06_center_83.mov  0.681602          0.654339     0.607156   \n",
-       "3          speaker_07_center_83.mov  0.666104          0.656836     0.567863   \n",
-       "4          speaker_10_center_83.mov  0.694171          0.596195     0.571414   \n",
-       "5          speaker_11_center_83.mov  0.712885          0.594764     0.571709   \n",
-       "6          speaker_15_center_83.mov  0.664158          0.670411      0.60421   \n",
-       "7          speaker_19_center_83.mov  0.761213          0.652635     0.651028   \n",
-       "8          speaker_23_center_83.mov  0.692788           0.68324     0.616737   \n",
-       "9          speaker_24_center_83.mov  0.705923          0.658382     0.610645   \n",
-       "10         speaker_27_center_83.mov  0.753417          0.708372     0.654608   \n",
-       "\n",
-       "          Agreeableness Non-Neuroticism  \n",
-       "Person ID                                \n",
-       "1              0.744589        0.488671  \n",
-       "2              0.731282        0.417908  \n",
-       "3              0.685067        0.378102  \n",
-       "4               0.66223        0.348639  \n",
-       "5              0.716696         0.37802  \n",
-       "6              0.696056        0.399842  \n",
-       "7              0.788677        0.459676  \n",
-       "8              0.795205        0.447242  \n",
-       "9              0.697415        0.411988  \n",
-       "10             0.816416        0.504743  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:13:30</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
+       "                Trait  Comfort  Camouflage  Assurance  Fashion  Individuality\n",
+       "ID                                                                           \n",
+       "1            Openness     0.01       -0.24       0.31     0.07           0.31\n",
+       "2   Conscientiousness    -0.03       -0.24       0.17     0.09           0.15\n",
+       "3        Extraversion    -0.01       -0.19       0.30     0.13           0.14\n",
+       "4       Agreeableness     0.16       -0.16       0.15    -0.09          -0.05\n",
+       "5     Non-Neuroticism     0.03       -0.16       0.01     0.00           0.06"
       ]
      },
+     "execution_count": 7,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644097?token=KGtSGMxjZtWXmBz&filename=df_%D1%81lothing_style_correlation.csv'\n",
+    "df_clothing_styles = pd.read_csv(url)\n",
+    "\n",
+    "df_clothing_styles.index.name = 'ID'\n",
+    "df_clothing_styles.index += 1\n",
+    "df_clothing_styles.index = df_clothing_styles.index.map(str)\n",
+    "\n",
+    "df_clothing_styles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d1f56a50",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -1727,15 +1652,27 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
-       "      <th>Mean</th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Priority 1</th>\n",
+       "      <th>Priority 2</th>\n",
+       "      <th>Priority 3</th>\n",
+       "      <th>Trait importance 1</th>\n",
+       "      <th>Trait importance 2</th>\n",
+       "      <th>Trait importance 3</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Metrics</th>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -1746,58 +1683,242 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>MAE</th>\n",
-       "      <td>0.0673</td>\n",
-       "      <td>0.0789</td>\n",
-       "      <td>0.1325</td>\n",
-       "      <td>0.102</td>\n",
-       "      <td>0.1002</td>\n",
-       "      <td>0.0962</td>\n",
+       "      <th>1</th>\n",
+       "      <td>2d6btbaNdfo.000.mp4</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Accuracy</th>\n",
-       "      <td>0.9327</td>\n",
-       "      <td>0.9211</td>\n",
-       "      <td>0.8675</td>\n",
-       "      <td>0.898</td>\n",
-       "      <td>0.8998</td>\n",
-       "      <td>0.9038</td>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
-       "Metrics                                                              \n",
-       "MAE         0.0673             0.0789        0.1325          0.102   \n",
-       "Accuracy    0.9327             0.9211        0.8675          0.898   \n",
-       "\n",
-       "          Non-Neuroticism    Mean  \n",
-       "Metrics                            \n",
-       "MAE                0.1002  0.0962  \n",
-       "Accuracy           0.8998  0.9038  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:13:30</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0962</span>, средняя точность: <span style=\"color:#1776D2\">0.9038</span> ...</span>** "
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.454</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>be0DQawtVkE.002.mp4</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>cLaZxEf1nE4.004.mp4</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
+       "      <td>0.558</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
+       "      <td>0.532</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
       ],
       "text/plain": [
-       "<IPython.core.display.Markdown object>"
+       "                          Path    OPE    CON    EXT    AGR   NNEU  Priority 1  \\\n",
+       "Person ID                                                                       \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601   Assurance   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431  Camouflage   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454  Camouflage   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587   Assurance   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642   Assurance   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587   Assurance   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507  Camouflage   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580     Comfort   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439  Camouflage   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606   Assurance   \n",
+       "\n",
+       "              Priority 2 Priority 3 Trait importance 1 Trait importance 2  \\\n",
+       "Person ID                                                                   \n",
+       "1          Individuality    Comfort           Openness  Conscientiousness   \n",
+       "2                Fashion    Comfort  Conscientiousness           Openness   \n",
+       "3                Fashion    Comfort  Conscientiousness           Openness   \n",
+       "4          Individuality    Comfort           Openness  Conscientiousness   \n",
+       "5          Individuality    Fashion           Openness       Extraversion   \n",
+       "6          Individuality    Fashion           Openness       Extraversion   \n",
+       "7          Individuality    Fashion      Agreeableness           Openness   \n",
+       "8          Individuality  Assurance           Openness      Agreeableness   \n",
+       "9                Comfort    Fashion  Conscientiousness           Openness   \n",
+       "10         Individuality    Comfort           Openness  Conscientiousness   \n",
+       "\n",
+       "          Trait importance 3  \n",
+       "Person ID                     \n",
+       "1              Agreeableness  \n",
+       "2            Non-Neuroticism  \n",
+       "3            Non-Neuroticism  \n",
+       "4              Agreeableness  \n",
+       "5          Conscientiousness  \n",
+       "6          Conscientiousness  \n",
+       "7            Non-Neuroticism  \n",
+       "8            Non-Neuroticism  \n",
+       "9            Non-Neuroticism  \n",
+       "10             Agreeableness  "
       ]
      },
+     "execution_count": 8,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._priority_calculation(\n",
+    "    correlation_coefficients = df_clothing_styles,\n",
+    "    col_name_ocean = 'Trait',\n",
+    "    threshold = 0.55,\n",
+    "    number_priority = 3,\n",
+    "    number_importance_traits = 3,\n",
+    "    out = True\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'clothing_styles_priorities_fi_en', out = True)\n",
+    "\n",
+    "# Опционно\n",
+    "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = ['OPE', 'CON', 'EXT', 'AGR', 'NNEU']\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2297292e-1e4b-44e0-9c85-ab0fba999892",
+   "metadata": {},
+   "source": [
+    "### `MuPTA` (ru)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3887d07c-eef2-4980-8d82-cabf6568aa7d",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:20:29</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1809,7 +1930,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 416.453 сек. ---**</span>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:20:30</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1818,147 +1939,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "import pandas as pd\n",
-    "\n",
-    "# Импорт модуля\n",
-    "from oceanai.modules.lab.build import Run\n",
-    "\n",
-    "# Создание экземпляра класса\n",
-    "_b5 = Run()\n",
-    "\n",
-    "corpus = 'mupta'\n",
-    "lang = 'ru'\n",
-    "\n",
-    "# Настройка ядра\n",
-    "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
-    "_b5.chunk_size_ = 2000000      # Размер загрузки файла из сети за 1 шаг\n",
-    "\n",
-    "# Формирование аудиомоделей\n",
-    "res_load_model_hc = _b5.load_audio_model_hc()\n",
-    "res_load_model_nn = _b5.load_audio_model_nn()\n",
-    "\n",
-    "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
-    "\n",
-    "# Формирование видеомоделей\n",
-    "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
-    "res_load_model_deep_fe = _b5.load_video_model_deep_fe()\n",
-    "res_load_model_nn = _b5.load_video_model_nn()\n",
-    "\n",
-    "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
-    "\n",
-    "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
-    "res_load_text_features = _b5.load_text_features()\n",
-    "\n",
-    "# Формирование текстовых моделей \n",
-    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
-    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
-    "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
-    "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
-    "\n",
-    "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
-    "\n",
-    "# Формирование модели для мультимодального объединения информации\n",
-    "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
-    "\n",
-    "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
-    "\n",
-    "PATH_TO_DIR = './video_MuPTA/'\n",
-    "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
-    "\n",
-    "_b5.path_to_save_ = PATH_SAVE_VIDEO\n",
-    "\n",
-    "# Загрузка 10 тестовых аудиовидеозаписей из корпуса MuPTA\n",
-    "# URL: https://hci.nw.ru/en/pages/mupta-corpus\n",
-    "domain = 'https://download.sberdisk.ru/download/file/'\n",
-    "tets_name_files = [\n",
-    "    '477995979?token=2cvyk7CS0mHx2MJ&filename=speaker_06_center_83.mov',\n",
-    "    '477995980?token=jGPtBPS69uzFU6Y&filename=speaker_01_center_83.mov',\n",
-    "    '477995967?token=zCaRbNB6ht5wMPq&filename=speaker_11_center_83.mov',\n",
-    "    '477995966?token=B1rbinDYRQKrI3T&filename=speaker_15_center_83.mov',\n",
-    "    '477995978?token=dEpVDtZg1EQiEQ9&filename=speaker_07_center_83.mov',\n",
-    "    '477995961?token=o1hVjw8G45q9L9Z&filename=speaker_19_center_83.mov',\n",
-    "    '477995964?token=5K220Aqf673VHPq&filename=speaker_23_center_83.mov',\n",
-    "    '477995965?token=v1LVD2KT1cU7Lpb&filename=speaker_24_center_83.mov',\n",
-    "    '477995962?token=tmaSGyyWLA6XCy9&filename=speaker_27_center_83.mov',\n",
-    "    '477995963?token=bTpo96qNDPcwGqb&filename=speaker_10_center_83.mov',\n",
-    "]\n",
-    "\n",
-    "for curr_files in tets_name_files:\n",
-    "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
-    "\n",
-    "# Получение прогнозов\n",
-    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
-    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
-    "\n",
-    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
-    "\n",
-    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "193025ae-0e9e-4a91-a3df-8f3bfc395a9d",
-   "metadata": {},
-   "source": [
-    "<hr>\n",
-    "\n",
-    "Для прогнозирования потребительских предпочтений в промышленных товарах необходимо знать коэффициенты корреляции, определяющие взаимосвязь между персональными качествами личности человека и предпочтениями в товарах или услугах.\n",
-    "\n",
-    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками автомобилей, представленными в статье:\n",
-    "\n",
-    "1) O'Connor P. J. et al. What Drives Consumer Automobile Choice? Investigating Personality Trait Predictors of Vehicle Preference Factors // Personality and Individual Differences. – 2022. – Vol. 184. – pp. 111220.\n",
-    "\n",
-    "Пользователь может установить свои коэффициенты корреляции."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1ef5d32b-bb48-4e0d-8cce-9d0cff815e80",
-   "metadata": {},
-   "source": [
-    "#### Прогнозирование потребительских предпочтений на характеристики атомобиля"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "f79ba8a2-c173-4d83-9cf7-d0c991c7bcc0",
-   "metadata": {},
-   "outputs": [
     {
      "data": {
       "text/html": [
@@ -1980,27 +1960,15 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Trait</th>\n",
-       "      <th>Performance</th>\n",
-       "      <th>Classic car features</th>\n",
-       "      <th>Luxury additions</th>\n",
-       "      <th>Fashion and attention</th>\n",
-       "      <th>Recreation</th>\n",
-       "      <th>Technology</th>\n",
-       "      <th>Family friendly</th>\n",
-       "      <th>Safe and reliable</th>\n",
-       "      <th>Practical and easy to use</th>\n",
-       "      <th>Economical/low cost</th>\n",
-       "      <th>Basic features</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>ID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -2012,142 +1980,141 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>Openness</td>\n",
-       "      <td>0.020000</td>\n",
-       "      <td>-0.033333</td>\n",
-       "      <td>-0.030000</td>\n",
-       "      <td>-0.050000</td>\n",
-       "      <td>0.033333</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>-0.030000</td>\n",
-       "      <td>0.136667</td>\n",
-       "      <td>0.106667</td>\n",
-       "      <td>0.093333</td>\n",
-       "      <td>0.006667</td>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.765745</td>\n",
+       "      <td>0.696637</td>\n",
+       "      <td>0.656309</td>\n",
+       "      <td>0.75986</td>\n",
+       "      <td>0.494141</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>-0.193333</td>\n",
-       "      <td>-0.063333</td>\n",
-       "      <td>-0.096667</td>\n",
-       "      <td>-0.096667</td>\n",
-       "      <td>0.086667</td>\n",
-       "      <td>-0.063333</td>\n",
-       "      <td>0.280000</td>\n",
-       "      <td>0.180000</td>\n",
-       "      <td>0.130000</td>\n",
-       "      <td>0.143333</td>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.686514</td>\n",
+       "      <td>0.659488</td>\n",
+       "      <td>0.611838</td>\n",
+       "      <td>0.749739</td>\n",
+       "      <td>0.420672</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>Extraversion</td>\n",
-       "      <td>0.133333</td>\n",
-       "      <td>0.060000</td>\n",
-       "      <td>0.106667</td>\n",
-       "      <td>0.123333</td>\n",
-       "      <td>0.126667</td>\n",
-       "      <td>0.120000</td>\n",
-       "      <td>0.090000</td>\n",
-       "      <td>0.136667</td>\n",
-       "      <td>0.043333</td>\n",
-       "      <td>0.073333</td>\n",
-       "      <td>0.050000</td>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.671993</td>\n",
+       "      <td>0.661216</td>\n",
+       "      <td>0.571759</td>\n",
+       "      <td>0.704542</td>\n",
+       "      <td>0.381026</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>-0.036667</td>\n",
-       "      <td>-0.193333</td>\n",
-       "      <td>-0.133333</td>\n",
-       "      <td>-0.133333</td>\n",
-       "      <td>-0.090000</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>-0.016667</td>\n",
-       "      <td>0.240000</td>\n",
-       "      <td>0.160000</td>\n",
-       "      <td>0.120000</td>\n",
-       "      <td>0.083333</td>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.69828</td>\n",
+       "      <td>0.59893</td>\n",
+       "      <td>0.571893</td>\n",
+       "      <td>0.674907</td>\n",
+       "      <td>0.35082</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>Non-Neuroticism</td>\n",
-       "      <td>0.016667</td>\n",
-       "      <td>-0.006667</td>\n",
-       "      <td>-0.010000</td>\n",
-       "      <td>-0.006667</td>\n",
-       "      <td>-0.033333</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>-0.023333</td>\n",
-       "      <td>0.093333</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>-0.040000</td>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718329</td>\n",
+       "      <td>0.598986</td>\n",
+       "      <td>0.573518</td>\n",
+       "      <td>0.73201</td>\n",
+       "      <td>0.379845</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.670932</td>\n",
+       "      <td>0.671055</td>\n",
+       "      <td>0.602337</td>\n",
+       "      <td>0.708656</td>\n",
+       "      <td>0.399527</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767261</td>\n",
+       "      <td>0.658167</td>\n",
+       "      <td>0.653367</td>\n",
+       "      <td>0.801366</td>\n",
+       "      <td>0.463443</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.699837</td>\n",
+       "      <td>0.684907</td>\n",
+       "      <td>0.616671</td>\n",
+       "      <td>0.806437</td>\n",
+       "      <td>0.447853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.710566</td>\n",
+       "      <td>0.66299</td>\n",
+       "      <td>0.610562</td>\n",
+       "      <td>0.711242</td>\n",
+       "      <td>0.413696</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759404</td>\n",
+       "      <td>0.712562</td>\n",
+       "      <td>0.658357</td>\n",
+       "      <td>0.830507</td>\n",
+       "      <td>0.507612</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Trait  Performance  Classic car features  Luxury additions  \\\n",
-       "ID                                                                           \n",
-       "1            Openness     0.020000             -0.033333         -0.030000   \n",
-       "2   Conscientiousness     0.013333             -0.193333         -0.063333   \n",
-       "3        Extraversion     0.133333              0.060000          0.106667   \n",
-       "4       Agreeableness    -0.036667             -0.193333         -0.133333   \n",
-       "5     Non-Neuroticism     0.016667             -0.006667         -0.010000   \n",
-       "\n",
-       "    Fashion and attention  Recreation  Technology  Family friendly  \\\n",
-       "ID                                                                   \n",
-       "1               -0.050000    0.033333    0.013333        -0.030000   \n",
-       "2               -0.096667   -0.096667    0.086667        -0.063333   \n",
-       "3                0.123333    0.126667    0.120000         0.090000   \n",
-       "4               -0.133333   -0.090000    0.046667        -0.016667   \n",
-       "5               -0.006667   -0.033333    0.046667        -0.023333   \n",
-       "\n",
-       "    Safe and reliable  Practical and easy to use  Economical/low cost  \\\n",
-       "ID                                                                      \n",
-       "1            0.136667                   0.106667             0.093333   \n",
-       "2            0.280000                   0.180000             0.130000   \n",
-       "3            0.136667                   0.043333             0.073333   \n",
-       "4            0.240000                   0.160000             0.120000   \n",
-       "5            0.093333                   0.046667             0.046667   \n",
+       "                               Path  Openness Conscientiousness Extraversion  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov  0.765745          0.696637     0.656309   \n",
+       "2          speaker_06_center_83.mov  0.686514          0.659488     0.611838   \n",
+       "3          speaker_07_center_83.mov  0.671993          0.661216     0.571759   \n",
+       "4          speaker_10_center_83.mov   0.69828           0.59893     0.571893   \n",
+       "5          speaker_11_center_83.mov  0.718329          0.598986     0.573518   \n",
+       "6          speaker_15_center_83.mov  0.670932          0.671055     0.602337   \n",
+       "7          speaker_19_center_83.mov  0.767261          0.658167     0.653367   \n",
+       "8          speaker_23_center_83.mov  0.699837          0.684907     0.616671   \n",
+       "9          speaker_24_center_83.mov  0.710566           0.66299     0.610562   \n",
+       "10         speaker_27_center_83.mov  0.759404          0.712562     0.658357   \n",
        "\n",
-       "    Basic features  \n",
-       "ID                  \n",
-       "1         0.006667  \n",
-       "2         0.143333  \n",
-       "3         0.050000  \n",
-       "4         0.083333  \n",
-       "5        -0.040000  "
+       "          Agreeableness Non-Neuroticism  \n",
+       "Person ID                                \n",
+       "1               0.75986        0.494141  \n",
+       "2              0.749739        0.420672  \n",
+       "3              0.704542        0.381026  \n",
+       "4              0.674907         0.35082  \n",
+       "5               0.73201        0.379845  \n",
+       "6              0.708656        0.399527  \n",
+       "7              0.801366        0.463443  \n",
+       "8              0.806437        0.447853  \n",
+       "9              0.711242        0.413696  \n",
+       "10             0.830507        0.507612  "
       ]
      },
-     "execution_count": 8,
      "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Загрузка датафрейма с коэффициентами корреляции\n",
-    "url = 'https://download.sberdisk.ru/download/file/478675818?token=EjfLMqOeK8cfnOu&filename=auto_characteristics.csv'\n",
-    "df_correlation_coefficients = pd.read_csv(url)\n",
-    "df_correlation_coefficients = pd.DataFrame(\n",
-    "    df_correlation_coefficients.drop(['Style and performance', 'Safety and practicality'], axis = 1)\n",
-    ")\n",
-    "df_correlation_coefficients.index.name = 'ID'\n",
-    "df_correlation_coefficients.index += 1\n",
-    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
-    "\n",
-    "df_correlation_coefficients"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "16e43257-3500-4dd8-b04a-34f7435fc185",
-   "metadata": {},
-   "outputs": [
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:20:30</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/html": [
@@ -2169,27 +2136,15 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>OPE</th>\n",
-       "      <th>CON</th>\n",
-       "      <th>EXT</th>\n",
-       "      <th>AGR</th>\n",
-       "      <th>NNEU</th>\n",
-       "      <th>Priority 1</th>\n",
-       "      <th>Priority 2</th>\n",
-       "      <th>Priority 3</th>\n",
-       "      <th>Trait importance 1</th>\n",
-       "      <th>Trait importance 2</th>\n",
-       "      <th>Trait importance 3</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Mean</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
+       "      <th>Metrics</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -2200,198 +2155,82 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
-       "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <th>MAE</th>\n",
+       "      <td>0.0706</td>\n",
+       "      <td>0.0788</td>\n",
+       "      <td>0.1328</td>\n",
+       "      <td>0.1071</td>\n",
+       "      <td>0.1002</td>\n",
+       "      <td>0.0979</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
-       "      <td>0.400</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
-       "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
-       "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
-       "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <th>Accuracy</th>\n",
+       "      <td>0.9294</td>\n",
+       "      <td>0.9212</td>\n",
+       "      <td>0.8672</td>\n",
+       "      <td>0.8929</td>\n",
+       "      <td>0.8998</td>\n",
+       "      <td>0.9021</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
-       "Person ID                                                                \n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489   \n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418   \n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378   \n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349   \n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378   \n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400   \n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460   \n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447   \n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412   \n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505   \n",
-       "\n",
-       "                  Priority 1                 Priority 2           Priority 3  \\\n",
-       "Person ID                                                                      \n",
-       "1          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "2          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "3          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "4          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "5          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "6          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "7          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "8          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "9          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
-       "10         Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
+       "Metrics                                                              \n",
+       "MAE         0.0706             0.0788        0.1328         0.1071   \n",
+       "Accuracy    0.9294             0.9212        0.8672         0.8929   \n",
        "\n",
-       "          Trait importance 1 Trait importance 2 Trait importance 3  \n",
-       "Person ID                                                           \n",
-       "1          Conscientiousness      Agreeableness           Openness  \n",
-       "2          Conscientiousness      Agreeableness           Openness  \n",
-       "3          Conscientiousness      Agreeableness           Openness  \n",
-       "4          Conscientiousness      Agreeableness           Openness  \n",
-       "5              Agreeableness  Conscientiousness           Openness  \n",
-       "6          Conscientiousness      Agreeableness           Openness  \n",
-       "7              Agreeableness  Conscientiousness           Openness  \n",
-       "8              Agreeableness  Conscientiousness           Openness  \n",
-       "9          Conscientiousness      Agreeableness           Openness  \n",
-       "10             Agreeableness  Conscientiousness           Openness  "
+       "          Non-Neuroticism    Mean  \n",
+       "Metrics                            \n",
+       "MAE                0.1002  0.0979  \n",
+       "Accuracy           0.8998  0.9021  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:20:30</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0979</span>, средняя точность: <span style=\"color:#1776D2\">0.9021</span> ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**--- Время выполнения: 324.067 сек. ---**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
       ]
      },
      "execution_count": 9,
@@ -2400,40 +2239,133 @@
     }
    ],
    "source": [
-    "_b5._priority_calculation(\n",
-    "    correlation_coefficients = df_correlation_coefficients,\n",
-    "    col_name_ocean = 'Trait',\n",
-    "    threshold = 0.55,\n",
-    "    number_priority = 3,\n",
-    "    number_importance_traits = 3,\n",
-    "    out = False\n",
-    ")\n",
+    "import os\n",
+    "import pandas as pd\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_priority_, name = 'auto_characteristics_priorities_mupta_ru', out = True)\n",
+    "# Импорт модуля\n",
+    "from oceanai.modules.lab.build import Run\n",
     "\n",
-    "# Опционно\n",
-    "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
-    "columns_to_round = ['OPE', 'CON', 'EXT', 'AGR', 'NNEU']\n",
-    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
-    "df"
+    "# Создание экземпляра класса\n",
+    "_b5 = Run()\n",
+    "\n",
+    "corpus = 'mupta'\n",
+    "lang = 'ru'\n",
+    "\n",
+    "# Настройка ядра\n",
+    "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
+    "_b5.chunk_size_ = 2000000      # Размер загрузки файла из сети за 1 шаг\n",
+    "\n",
+    "# Формирование аудиомоделей\n",
+    "res_load_model_hc = _b5.load_audio_model_hc()\n",
+    "res_load_model_nn = _b5.load_audio_model_nn()\n",
+    "\n",
+    "# Загрузка весов аудиомоделей\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Формирование видеомоделей\n",
+    "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
+    "res_load_model_deep_fe = _b5.load_video_model_deep_fe()\n",
+    "res_load_model_nn = _b5.load_video_model_nn()\n",
+    "\n",
+    "# Загрузка весов видеомоделей\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
+    "res_load_text_features = _b5.load_text_features()\n",
+    "\n",
+    "# Формирование текстовых моделей \n",
+    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
+    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
+    "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
+    "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
+    "\n",
+    "# Загрузка весов текстовых моделей\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Формирование модели для мультимодального объединения информации\n",
+    "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
+    "\n",
+    "# Загрузка весов модели для мультимодального объединения информации\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
+    "\n",
+    "PATH_TO_DIR = './video_MuPTA/'\n",
+    "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
+    "\n",
+    "_b5.path_to_save_ = PATH_SAVE_VIDEO\n",
+    "\n",
+    "# Загрузка 10 тестовых аудиовидеозаписей из корпуса MuPTA\n",
+    "# URL: https://hci.nw.ru/en/pages/mupta-corpus\n",
+    "domain = 'https://download.sberdisk.ru/download/file/'\n",
+    "tets_name_files = [\n",
+    "    '477995979?token=2cvyk7CS0mHx2MJ&filename=speaker_06_center_83.mov',\n",
+    "    '477995980?token=jGPtBPS69uzFU6Y&filename=speaker_01_center_83.mov',\n",
+    "    '477995967?token=zCaRbNB6ht5wMPq&filename=speaker_11_center_83.mov',\n",
+    "    '477995966?token=B1rbinDYRQKrI3T&filename=speaker_15_center_83.mov',\n",
+    "    '477995978?token=dEpVDtZg1EQiEQ9&filename=speaker_07_center_83.mov',\n",
+    "    '477995961?token=o1hVjw8G45q9L9Z&filename=speaker_19_center_83.mov',\n",
+    "    '477995964?token=5K220Aqf673VHPq&filename=speaker_23_center_83.mov',\n",
+    "    '477995965?token=v1LVD2KT1cU7Lpb&filename=speaker_24_center_83.mov',\n",
+    "    '477995962?token=tmaSGyyWLA6XCy9&filename=speaker_27_center_83.mov',\n",
+    "    '477995963?token=bTpo96qNDPcwGqb&filename=speaker_10_center_83.mov',\n",
+    "]\n",
+    "\n",
+    "for curr_files in tets_name_files:\n",
+    "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
+    "\n",
+    "# Получение прогнозов\n",
+    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
+    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "\n",
+    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
+    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "\n",
+    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "78e820f4-3f3d-43d2-b9b8-76d4b21efb78",
+   "id": "193025ae-0e9e-4a91-a3df-8f3bfc395a9d",
    "metadata": {},
    "source": [
-    "#### Прогнозирование потребительских предпочтений на характеристики мобильного устройства\n",
+    "<hr>\n",
     "\n",
-    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками мобильного устройства, представленными в статье:\n",
+    "Для прогнозирования потребительских предпочтений в промышленных товарах необходимо знать коэффициенты корреляции, определяющие взаимосвязь между персональными качествами личности человека и предпочтениями в товарах или услугах.\n",
     "\n",
-    "1) Peltonen E., Sharmila P., Asare K. O., Visuri A., Lagerspetz E., Ferreira D. (2020). When phones get personal: Predicting Big Five personality traits from application usage // Pervasive and Mobile Computing. – 2020. – Vol. 69. – 101269."
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками автомобилей, представленными в статье:\n",
+    "\n",
+    "1) O'Connor P. J. et al. What Drives Consumer Automobile Choice? Investigating Personality Trait Predictors of Vehicle Preference Factors // Personality and Individual Differences. – 2022. – Vol. 184. – pp. 111220.\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1ef5d32b-bb48-4e0d-8cce-9d0cff815e80",
+   "metadata": {},
+   "source": [
+    "#### Прогнозирование потребительских предпочтений на характеристики атомобиля"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "069f1f9d-18c1-42a8-89b9-0f9659544210",
+   "id": "f79ba8a2-c173-4d83-9cf7-d0c991c7bcc0",
    "metadata": {},
    "outputs": [
     {
@@ -2458,22 +2390,17 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Trait</th>\n",
-       "      <th>Communication</th>\n",
-       "      <th>Game Action</th>\n",
-       "      <th>Game Board</th>\n",
-       "      <th>Game Casino</th>\n",
-       "      <th>Game Educational</th>\n",
-       "      <th>Game Simulation</th>\n",
-       "      <th>Game Trivia</th>\n",
-       "      <th>Entertainment</th>\n",
-       "      <th>Finance</th>\n",
-       "      <th>Health and Fitness</th>\n",
-       "      <th>Media and Video</th>\n",
-       "      <th>Music and Audio</th>\n",
-       "      <th>News and Magazines</th>\n",
-       "      <th>Personalisation</th>\n",
-       "      <th>Travel and Local</th>\n",
-       "      <th>Weather</th>\n",
+       "      <th>Performance</th>\n",
+       "      <th>Classic car features</th>\n",
+       "      <th>Luxury additions</th>\n",
+       "      <th>Fashion and attention</th>\n",
+       "      <th>Recreation</th>\n",
+       "      <th>Technology</th>\n",
+       "      <th>Family friendly</th>\n",
+       "      <th>Safe and reliable</th>\n",
+       "      <th>Practical and easy to use</th>\n",
+       "      <th>Economical/low cost</th>\n",
+       "      <th>Basic features</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ID</th>\n",
@@ -2489,150 +2416,120 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Openness</td>\n",
-       "      <td>0.118</td>\n",
-       "      <td>0.056</td>\n",
-       "      <td>0.079</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.027</td>\n",
-       "      <td>0.104</td>\n",
-       "      <td>0.026</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.006</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.004</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>-0.033333</td>\n",
+       "      <td>-0.030000</td>\n",
+       "      <td>-0.050000</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>-0.030000</td>\n",
+       "      <td>0.136667</td>\n",
+       "      <td>0.106667</td>\n",
+       "      <td>0.093333</td>\n",
+       "      <td>0.006667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>0.119</td>\n",
-       "      <td>0.043</td>\n",
-       "      <td>0.107</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>0.039</td>\n",
-       "      <td>0.012</td>\n",
-       "      <td>0.119</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.005</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>-0.193333</td>\n",
+       "      <td>-0.063333</td>\n",
+       "      <td>-0.096667</td>\n",
+       "      <td>-0.096667</td>\n",
+       "      <td>0.086667</td>\n",
+       "      <td>-0.063333</td>\n",
+       "      <td>0.280000</td>\n",
+       "      <td>0.180000</td>\n",
+       "      <td>0.130000</td>\n",
+       "      <td>0.143333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Extraversion</td>\n",
-       "      <td>0.246</td>\n",
-       "      <td>0.182</td>\n",
-       "      <td>0.211</td>\n",
-       "      <td>0.311</td>\n",
-       "      <td>0.102</td>\n",
-       "      <td>0.165</td>\n",
-       "      <td>0.223</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.009</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>0.133333</td>\n",
+       "      <td>0.060000</td>\n",
+       "      <td>0.106667</td>\n",
+       "      <td>0.123333</td>\n",
+       "      <td>0.126667</td>\n",
+       "      <td>0.120000</td>\n",
+       "      <td>0.090000</td>\n",
+       "      <td>0.136667</td>\n",
+       "      <td>0.043333</td>\n",
+       "      <td>0.073333</td>\n",
+       "      <td>0.050000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>0.218</td>\n",
-       "      <td>0.104</td>\n",
-       "      <td>0.164</td>\n",
-       "      <td>0.284</td>\n",
-       "      <td>0.165</td>\n",
-       "      <td>0.122</td>\n",
-       "      <td>0.162</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>-0.036667</td>\n",
+       "      <td>-0.193333</td>\n",
+       "      <td>-0.133333</td>\n",
+       "      <td>-0.133333</td>\n",
+       "      <td>-0.090000</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>-0.016667</td>\n",
+       "      <td>0.240000</td>\n",
+       "      <td>0.160000</td>\n",
+       "      <td>0.120000</td>\n",
+       "      <td>0.083333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>Non-Neuroticism</td>\n",
-       "      <td>0.046</td>\n",
-       "      <td>0.047</td>\n",
-       "      <td>0.125</td>\n",
-       "      <td>0.515</td>\n",
-       "      <td>0.272</td>\n",
-       "      <td>0.179</td>\n",
-       "      <td>0.214</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.030</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.005</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.008</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.007</td>\n",
+       "      <td>0.016667</td>\n",
+       "      <td>-0.006667</td>\n",
+       "      <td>-0.010000</td>\n",
+       "      <td>-0.006667</td>\n",
+       "      <td>-0.033333</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>-0.023333</td>\n",
+       "      <td>0.093333</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>-0.040000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Trait  Communication  Game Action  Game Board  Game Casino  \\\n",
+       "                Trait  Performance  Classic car features  Luxury additions  \\\n",
        "ID                                                                           \n",
-       "1            Openness          0.118        0.056       0.079        0.342   \n",
-       "2   Conscientiousness          0.119        0.043       0.107        0.448   \n",
-       "3        Extraversion          0.246        0.182       0.211        0.311   \n",
-       "4       Agreeableness          0.218        0.104       0.164        0.284   \n",
-       "5     Non-Neuroticism          0.046        0.047       0.125        0.515   \n",
+       "1            Openness     0.020000             -0.033333         -0.030000   \n",
+       "2   Conscientiousness     0.013333             -0.193333         -0.063333   \n",
+       "3        Extraversion     0.133333              0.060000          0.106667   \n",
+       "4       Agreeableness    -0.036667             -0.193333         -0.133333   \n",
+       "5     Non-Neuroticism     0.016667             -0.006667         -0.010000   \n",
        "\n",
-       "    Game Educational  Game Simulation  Game Trivia  Entertainment  Finance  \\\n",
-       "ID                                                                           \n",
-       "1              0.027            0.104        0.026          0.000    0.006   \n",
-       "2              0.039            0.012        0.119          0.000    0.005   \n",
-       "3              0.102            0.165        0.223          0.001    0.003   \n",
-       "4              0.165            0.122        0.162          0.000    0.003   \n",
-       "5              0.272            0.179        0.214          0.002    0.030   \n",
+       "    Fashion and attention  Recreation  Technology  Family friendly  \\\n",
+       "ID                                                                   \n",
+       "1               -0.050000    0.033333    0.013333        -0.030000   \n",
+       "2               -0.096667   -0.096667    0.086667        -0.063333   \n",
+       "3                0.123333    0.126667    0.120000         0.090000   \n",
+       "4               -0.133333   -0.090000    0.046667        -0.016667   \n",
+       "5               -0.006667   -0.033333    0.046667        -0.023333   \n",
        "\n",
-       "    Health and Fitness  Media and Video  Music and Audio  News and Magazines  \\\n",
-       "ID                                                                             \n",
-       "1                0.002            0.000            0.000               0.001   \n",
-       "2                0.001            0.000            0.002               0.002   \n",
-       "3                0.000            0.001            0.001               0.001   \n",
-       "4                0.001            0.000            0.002               0.002   \n",
-       "5                0.001            0.000            0.005               0.003   \n",
+       "    Safe and reliable  Practical and easy to use  Economical/low cost  \\\n",
+       "ID                                                                      \n",
+       "1            0.136667                   0.106667             0.093333   \n",
+       "2            0.280000                   0.180000             0.130000   \n",
+       "3            0.136667                   0.043333             0.073333   \n",
+       "4            0.240000                   0.160000             0.120000   \n",
+       "5            0.093333                   0.046667             0.046667   \n",
        "\n",
-       "    Personalisation  Travel and Local  Weather  \n",
-       "ID                                              \n",
-       "1             0.004             0.002    0.004  \n",
-       "2             0.001             0.001    0.003  \n",
-       "3             0.004             0.009    0.003  \n",
-       "4             0.001             0.004    0.003  \n",
-       "5             0.008             0.004    0.007  "
+       "    Basic features  \n",
+       "ID                  \n",
+       "1         0.006667  \n",
+       "2         0.143333  \n",
+       "3         0.050000  \n",
+       "4         0.083333  \n",
+       "5        -0.040000  "
       ]
      },
      "execution_count": 10,
@@ -2642,20 +2539,22 @@
    ],
    "source": [
     "# Загрузка датафрейма с коэффициентами корреляции\n",
-    "url = 'https://download.sberdisk.ru/download/file/478676690?token=7KcAxPqMpWiYQnx&filename=divice_characteristics.csv'\n",
-    "df_divice_characteristics = pd.read_csv(url)\n",
-    "\n",
-    "df_divice_characteristics.index.name = 'ID'\n",
-    "df_divice_characteristics.index += 1\n",
-    "df_divice_characteristics.index = df_divice_characteristics.index.map(str)\n",
+    "url = 'https://download.sberdisk.ru/download/file/478675818?token=EjfLMqOeK8cfnOu&filename=auto_characteristics.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "df_correlation_coefficients = pd.DataFrame(\n",
+    "    df_correlation_coefficients.drop(['Style and performance', 'Safety and practicality'], axis = 1)\n",
+    ")\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
     "\n",
-    "df_divice_characteristics"
+    "df_correlation_coefficients"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "08e50bb5-6da8-493f-9f3d-3bb1dbf0f5dc",
+   "id": "16e43257-3500-4dd8-b04a-34f7435fc185",
    "metadata": {},
    "outputs": [
     {
@@ -2712,152 +2611,152 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
-       "      <td>Extraversion</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
-       "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
        "      <td>0.400</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
-       "      <td>Extraversion</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
        "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
        "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
        "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
-       "      <td>Extraversion</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Board</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -2866,42 +2765,42 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489   \n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418   \n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378   \n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349   \n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378   \n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400   \n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460   \n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447   \n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412   \n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505   \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
        "\n",
-       "            Priority 1     Priority 2  Priority 3 Trait importance 1  \\\n",
-       "Person ID                                                              \n",
-       "1          Game Casino  Communication  Game Board       Extraversion   \n",
-       "2          Game Casino  Communication  Game Board      Agreeableness   \n",
-       "3          Game Casino  Communication  Game Board      Agreeableness   \n",
-       "4          Game Casino  Communication  Game Board      Agreeableness   \n",
-       "5          Game Casino  Communication  Game Board      Agreeableness   \n",
-       "6          Game Casino  Communication  Game Board       Extraversion   \n",
-       "7          Game Casino  Communication  Game Board      Agreeableness   \n",
-       "8          Game Casino  Communication  Game Board      Agreeableness   \n",
-       "9          Game Casino  Communication  Game Board       Extraversion   \n",
-       "10         Game Casino  Communication  Game Board      Agreeableness   \n",
+       "                  Priority 1                 Priority 2           Priority 3  \\\n",
+       "Person ID                                                                      \n",
+       "1          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "2          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "3          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "4          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "5          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "6          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "7          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "8          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "9          Safe and reliable  Practical and easy to use  Economical/low cost   \n",
+       "10         Safe and reliable  Practical and easy to use  Economical/low cost   \n",
        "\n",
-       "          Trait importance 2 Trait importance 3  \n",
-       "Person ID                                        \n",
-       "1              Agreeableness  Conscientiousness  \n",
-       "2               Extraversion  Conscientiousness  \n",
-       "3          Conscientiousness       Extraversion  \n",
-       "4               Extraversion  Conscientiousness  \n",
-       "5               Extraversion  Conscientiousness  \n",
-       "6              Agreeableness  Conscientiousness  \n",
-       "7               Extraversion  Conscientiousness  \n",
-       "8               Extraversion  Conscientiousness  \n",
-       "9              Agreeableness  Conscientiousness  \n",
-       "10              Extraversion  Conscientiousness  "
+       "          Trait importance 1 Trait importance 2 Trait importance 3  \n",
+       "Person ID                                                           \n",
+       "1          Conscientiousness      Agreeableness           Openness  \n",
+       "2              Agreeableness  Conscientiousness           Openness  \n",
+       "3          Conscientiousness      Agreeableness           Openness  \n",
+       "4          Conscientiousness      Agreeableness           Openness  \n",
+       "5              Agreeableness  Conscientiousness           Openness  \n",
+       "6          Conscientiousness      Agreeableness           Openness  \n",
+       "7              Agreeableness  Conscientiousness           Openness  \n",
+       "8              Agreeableness  Conscientiousness           Openness  \n",
+       "9          Conscientiousness      Agreeableness           Openness  \n",
+       "10             Agreeableness  Conscientiousness           Openness  "
       ]
      },
      "execution_count": 11,
@@ -2911,15 +2810,15 @@
    ],
    "source": [
     "_b5._priority_calculation(\n",
-    "    correlation_coefficients = df_divice_characteristics,\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
     "    col_name_ocean = 'Trait',\n",
     "    threshold = 0.55,\n",
     "    number_priority = 3,\n",
     "    number_importance_traits = 3,\n",
-    "    out = True\n",
+    "    out = False\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_priority_, name = 'divice_characteristics_priorities_mupta_ru', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'auto_characteristics_priorities_mupta_ru', out = True)\n",
     "\n",
     "# Опционно\n",
     "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
@@ -2930,42 +2829,22 @@
   },
   {
    "cell_type": "markdown",
-   "id": "708fcd2b-eb78-4f58-96d2-19298b8c26d9",
+   "id": "78e820f4-3f3d-43d2-b9b8-76d4b21efb78",
    "metadata": {},
    "source": [
-    "### `MuPTA` (en)"
+    "#### Прогнозирование потребительских предпочтений на характеристики мобильного устройства\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками мобильного устройства, представленными в статье:\n",
+    "\n",
+    "1) Peltonen E., Sharmila P., Asare K. O., Visuri A., Lagerspetz E., Ferreira D. (2020). When phones get personal: Predicting Big Five personality traits from application usage // Pervasive and Mobile Computing. – 2020. – Vol. 69. – 101269."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "1b1f1294-6f09-4827-85c6-75ccc7fbd375",
+   "id": "069f1f9d-18c1-42a8-89b9-0f9659544210",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:20:55</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:20:57</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/html": [
@@ -2987,15 +2866,37 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>Communication</th>\n",
+       "      <th>Game Action</th>\n",
+       "      <th>Game Board</th>\n",
+       "      <th>Game Casino</th>\n",
+       "      <th>Game Educational</th>\n",
+       "      <th>Game Simulation</th>\n",
+       "      <th>Game Trivia</th>\n",
+       "      <th>Entertainment</th>\n",
+       "      <th>Finance</th>\n",
+       "      <th>Health and Fitness</th>\n",
+       "      <th>Media and Video</th>\n",
+       "      <th>Music and Audio</th>\n",
+       "      <th>News and Magazines</th>\n",
+       "      <th>Personalisation</th>\n",
+       "      <th>Travel and Local</th>\n",
+       "      <th>Weather</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -3007,141 +2908,165 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.564985</td>\n",
-       "      <td>0.539052</td>\n",
-       "      <td>0.440615</td>\n",
-       "      <td>0.59251</td>\n",
-       "      <td>0.488763</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.118</td>\n",
+       "      <td>0.056</td>\n",
+       "      <td>0.079</td>\n",
+       "      <td>0.342</td>\n",
+       "      <td>0.027</td>\n",
+       "      <td>0.104</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.650774</td>\n",
-       "      <td>0.663849</td>\n",
-       "      <td>0.607308</td>\n",
-       "      <td>0.643847</td>\n",
-       "      <td>0.620627</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.119</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>0.107</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.039</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>0.119</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.435976</td>\n",
-       "      <td>0.486683</td>\n",
-       "      <td>0.313828</td>\n",
-       "      <td>0.415446</td>\n",
-       "      <td>0.396618</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.246</td>\n",
+       "      <td>0.182</td>\n",
+       "      <td>0.211</td>\n",
+       "      <td>0.311</td>\n",
+       "      <td>0.102</td>\n",
+       "      <td>0.165</td>\n",
+       "      <td>0.223</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.498542</td>\n",
-       "      <td>0.511243</td>\n",
-       "      <td>0.412592</td>\n",
-       "      <td>0.468947</td>\n",
-       "      <td>0.44399</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.394776</td>\n",
-       "      <td>0.341608</td>\n",
-       "      <td>0.327082</td>\n",
-       "      <td>0.427304</td>\n",
-       "      <td>0.354936</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566107</td>\n",
-       "      <td>0.543811</td>\n",
-       "      <td>0.492766</td>\n",
-       "      <td>0.587411</td>\n",
-       "      <td>0.499433</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506271</td>\n",
-       "      <td>0.438215</td>\n",
-       "      <td>0.430894</td>\n",
-       "      <td>0.456177</td>\n",
-       "      <td>0.44075</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486463</td>\n",
-       "      <td>0.521755</td>\n",
-       "      <td>0.309894</td>\n",
-       "      <td>0.432291</td>\n",
-       "      <td>0.433601</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417404</td>\n",
-       "      <td>0.473339</td>\n",
-       "      <td>0.320714</td>\n",
-       "      <td>0.445086</td>\n",
-       "      <td>0.414649</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.218</td>\n",
+       "      <td>0.104</td>\n",
+       "      <td>0.164</td>\n",
+       "      <td>0.284</td>\n",
+       "      <td>0.165</td>\n",
+       "      <td>0.122</td>\n",
+       "      <td>0.162</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526112</td>\n",
-       "      <td>0.661107</td>\n",
-       "      <td>0.443167</td>\n",
-       "      <td>0.558965</td>\n",
-       "      <td>0.554224</td>\n",
+       "      <th>5</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.046</td>\n",
+       "      <td>0.047</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.272</td>\n",
+       "      <td>0.179</td>\n",
+       "      <td>0.214</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.030</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.007</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path  Openness Conscientiousness Extraversion  \\\n",
-       "Person ID                                                                      \n",
-       "1          speaker_01_center_83.mov  0.564985          0.539052     0.440615   \n",
-       "2          speaker_06_center_83.mov  0.650774          0.663849     0.607308   \n",
-       "3          speaker_07_center_83.mov  0.435976          0.486683     0.313828   \n",
-       "4          speaker_10_center_83.mov  0.498542          0.511243     0.412592   \n",
-       "5          speaker_11_center_83.mov  0.394776          0.341608     0.327082   \n",
-       "6          speaker_15_center_83.mov  0.566107          0.543811     0.492766   \n",
-       "7          speaker_19_center_83.mov  0.506271          0.438215     0.430894   \n",
-       "8          speaker_23_center_83.mov  0.486463          0.521755     0.309894   \n",
-       "9          speaker_24_center_83.mov  0.417404          0.473339     0.320714   \n",
-       "10         speaker_27_center_83.mov  0.526112          0.661107     0.443167   \n",
+       "                Trait  Communication  Game Action  Game Board  Game Casino  \\\n",
+       "ID                                                                           \n",
+       "1            Openness          0.118        0.056       0.079        0.342   \n",
+       "2   Conscientiousness          0.119        0.043       0.107        0.448   \n",
+       "3        Extraversion          0.246        0.182       0.211        0.311   \n",
+       "4       Agreeableness          0.218        0.104       0.164        0.284   \n",
+       "5     Non-Neuroticism          0.046        0.047       0.125        0.515   \n",
        "\n",
-       "          Agreeableness Non-Neuroticism  \n",
-       "Person ID                                \n",
-       "1               0.59251        0.488763  \n",
-       "2              0.643847        0.620627  \n",
-       "3              0.415446        0.396618  \n",
-       "4              0.468947         0.44399  \n",
-       "5              0.427304        0.354936  \n",
-       "6              0.587411        0.499433  \n",
-       "7              0.456177         0.44075  \n",
-       "8              0.432291        0.433601  \n",
-       "9              0.445086        0.414649  \n",
-       "10             0.558965        0.554224  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:20:57</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
+       "    Game Educational  Game Simulation  Game Trivia  Entertainment  Finance  \\\n",
+       "ID                                                                           \n",
+       "1              0.027            0.104        0.026          0.000    0.006   \n",
+       "2              0.039            0.012        0.119          0.000    0.005   \n",
+       "3              0.102            0.165        0.223          0.001    0.003   \n",
+       "4              0.165            0.122        0.162          0.000    0.003   \n",
+       "5              0.272            0.179        0.214          0.002    0.030   \n",
+       "\n",
+       "    Health and Fitness  Media and Video  Music and Audio  News and Magazines  \\\n",
+       "ID                                                                             \n",
+       "1                0.002            0.000            0.000               0.001   \n",
+       "2                0.001            0.000            0.002               0.002   \n",
+       "3                0.000            0.001            0.001               0.001   \n",
+       "4                0.001            0.000            0.002               0.002   \n",
+       "5                0.001            0.000            0.005               0.003   \n",
+       "\n",
+       "    Personalisation  Travel and Local  Weather  \n",
+       "ID                                              \n",
+       "1             0.004             0.002    0.004  \n",
+       "2             0.001             0.001    0.003  \n",
+       "3             0.004             0.009    0.003  \n",
+       "4             0.001             0.004    0.003  \n",
+       "5             0.008             0.004    0.007  "
       ]
      },
+     "execution_count": 12,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/478676690?token=7KcAxPqMpWiYQnx&filename=divice_characteristics.csv'\n",
+    "df_divice_characteristics = pd.read_csv(url)\n",
+    "\n",
+    "df_divice_characteristics.index.name = 'ID'\n",
+    "df_divice_characteristics.index += 1\n",
+    "df_divice_characteristics.index = df_divice_characteristics.index.map(str)\n",
+    "\n",
+    "df_divice_characteristics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "08e50bb5-6da8-493f-9f3d-3bb1dbf0f5dc",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -3163,15 +3088,27 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
-       "      <th>Mean</th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Priority 1</th>\n",
+       "      <th>Priority 2</th>\n",
+       "      <th>Priority 3</th>\n",
+       "      <th>Trait importance 1</th>\n",
+       "      <th>Trait importance 2</th>\n",
+       "      <th>Trait importance 3</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Metrics</th>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -3182,217 +3119,1588 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>MAE</th>\n",
-       "      <td>0.1727</td>\n",
-       "      <td>0.1672</td>\n",
-       "      <td>0.1661</td>\n",
-       "      <td>0.2579</td>\n",
-       "      <td>0.107</td>\n",
-       "      <td>0.1742</td>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Accuracy</th>\n",
-       "      <td>0.8273</td>\n",
-       "      <td>0.8328</td>\n",
-       "      <td>0.8339</td>\n",
-       "      <td>0.7421</td>\n",
-       "      <td>0.893</td>\n",
-       "      <td>0.8258</td>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
-       "Metrics                                                              \n",
-       "MAE         0.1727             0.1672        0.1661         0.2579   \n",
-       "Accuracy    0.8273             0.8328        0.8339         0.7421   \n",
-       "\n",
-       "          Non-Neuroticism    Mean  \n",
-       "Metrics                            \n",
-       "MAE                 0.107  0.1742  \n",
-       "Accuracy            0.893  0.8258  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:20:57</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.1742</span>, средняя точность: <span style=\"color:#1776D2\">0.8258</span> ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 379.936 сек. ---**</span>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "import pandas as pd\n",
-    "\n",
-    "# Импорт модуля\n",
-    "from oceanai.modules.lab.build import Run\n",
-    "\n",
-    "# Создание экземпляра класса\n",
-    "_b5 = Run()\n",
-    "\n",
-    "corpus = 'fi'\n",
-    "lang = 'en'\n",
-    "\n",
-    "# Настройка ядра\n",
-    "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
-    "_b5.chunk_size_ = 2000000      # Размер загрузки файла из сети за 1 шаг\n",
-    "\n",
-    "# Формирование аудиомоделей\n",
-    "res_load_model_hc = _b5.load_audio_model_hc()\n",
-    "res_load_model_nn = _b5.load_audio_model_nn()\n",
-    "\n",
-    "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
-    "\n",
-    "# Формирование видеомоделей\n",
-    "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
-    "res_load_model_deep_fe = _b5.load_video_model_deep_fe()\n",
-    "res_load_model_nn = _b5.load_video_model_nn()\n",
-    "\n",
-    "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
-    "\n",
-    "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
-    "res_load_text_features = _b5.load_text_features()\n",
-    "\n",
-    "# Формирование текстовых моделей \n",
-    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
-    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
-    "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
-    "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
-    "\n",
-    "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "\n",
+       "            Priority 1     Priority 2  Priority 3 Trait importance 1  \\\n",
+       "Person ID                                                              \n",
+       "1          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "2          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "3          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "4          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "5          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "6          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "7          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "8          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "9          Game Casino  Communication  Game Board      Agreeableness   \n",
+       "10         Game Casino  Communication  Game Board      Agreeableness   \n",
+       "\n",
+       "          Trait importance 2 Trait importance 3  \n",
+       "Person ID                                        \n",
+       "1               Extraversion  Conscientiousness  \n",
+       "2               Extraversion  Conscientiousness  \n",
+       "3          Conscientiousness       Extraversion  \n",
+       "4               Extraversion  Conscientiousness  \n",
+       "5               Extraversion  Conscientiousness  \n",
+       "6               Extraversion  Conscientiousness  \n",
+       "7               Extraversion  Conscientiousness  \n",
+       "8               Extraversion  Conscientiousness  \n",
+       "9               Extraversion  Conscientiousness  \n",
+       "10              Extraversion  Conscientiousness  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._priority_calculation(\n",
+    "    correlation_coefficients = df_divice_characteristics,\n",
+    "    col_name_ocean = 'Trait',\n",
+    "    threshold = 0.55,\n",
+    "    number_priority = 3,\n",
+    "    number_importance_traits = 3,\n",
+    "    out = True\n",
+    ")\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'divice_characteristics_priorities_mupta_ru', out = True)\n",
     "\n",
-    "# Формирование модели для мультимодального объединения информации\n",
-    "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
+    "# Опционно\n",
+    "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = ['OPE', 'CON', 'EXT', 'AGR', 'NNEU']\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "60880e10",
+   "metadata": {},
+   "source": [
+    "#### Прогнозирование потребительских предпочтений по стилю одежды\n",
     "\n",
-    "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и стилем одежды, представленными в статье:\n",
     "\n",
-    "PATH_TO_DIR = './video_MuPTA/'\n",
-    "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
+    "1) Stolovy T. Styling the self: clothing practices, personality traits, and body image among Israeli women // Frontiers in psychology. - 2022. - vol. 12. - 719318."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "34535a08",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>Comfort</th>\n",
+       "      <th>Camouflage</th>\n",
+       "      <th>Assurance</th>\n",
+       "      <th>Fashion</th>\n",
+       "      <th>Individuality</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.24</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.24</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>-0.01</td>\n",
+       "      <td>-0.19</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>-0.16</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>-0.09</td>\n",
+       "      <td>-0.05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>-0.16</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.06</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Trait  Comfort  Camouflage  Assurance  Fashion  Individuality\n",
+       "ID                                                                           \n",
+       "1            Openness     0.01       -0.24       0.31     0.07           0.31\n",
+       "2   Conscientiousness    -0.03       -0.24       0.17     0.09           0.15\n",
+       "3        Extraversion    -0.01       -0.19       0.30     0.13           0.14\n",
+       "4       Agreeableness     0.16       -0.16       0.15    -0.09          -0.05\n",
+       "5     Non-Neuroticism     0.03       -0.16       0.01     0.00           0.06"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644097?token=KGtSGMxjZtWXmBz&filename=df_%D1%81lothing_style_correlation.csv'\n",
+    "df_clothing_styles = pd.read_csv(url)\n",
     "\n",
-    "_b5.path_to_save_ = PATH_SAVE_VIDEO\n",
+    "df_clothing_styles.index.name = 'ID'\n",
+    "df_clothing_styles.index += 1\n",
+    "df_clothing_styles.index = df_clothing_styles.index.map(str)\n",
     "\n",
-    "# Загрузка 10 тестовых аудиовидеозаписей из корпуса MuPTA\n",
-    "# URL: https://hci.nw.ru/en/pages/mupta-corpus\n",
-    "domain = 'https://download.sberdisk.ru/download/file/'\n",
-    "tets_name_files = [\n",
-    "    '477995979?token=2cvyk7CS0mHx2MJ&filename=speaker_06_center_83.mov',\n",
-    "    '477995980?token=jGPtBPS69uzFU6Y&filename=speaker_01_center_83.mov',\n",
-    "    '477995967?token=zCaRbNB6ht5wMPq&filename=speaker_11_center_83.mov',\n",
-    "    '477995966?token=B1rbinDYRQKrI3T&filename=speaker_15_center_83.mov',\n",
-    "    '477995978?token=dEpVDtZg1EQiEQ9&filename=speaker_07_center_83.mov',\n",
-    "    '477995961?token=o1hVjw8G45q9L9Z&filename=speaker_19_center_83.mov',\n",
-    "    '477995964?token=5K220Aqf673VHPq&filename=speaker_23_center_83.mov',\n",
-    "    '477995965?token=v1LVD2KT1cU7Lpb&filename=speaker_24_center_83.mov',\n",
-    "    '477995962?token=tmaSGyyWLA6XCy9&filename=speaker_27_center_83.mov',\n",
-    "    '477995963?token=bTpo96qNDPcwGqb&filename=speaker_10_center_83.mov',\n",
-    "]\n",
+    "df_clothing_styles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "eb95138b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Priority 1</th>\n",
+       "      <th>Priority 2</th>\n",
+       "      <th>Priority 3</th>\n",
+       "      <th>Trait importance 1</th>\n",
+       "      <th>Trait importance 2</th>\n",
+       "      <th>Trait importance 3</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "\n",
+       "          Priority 1     Priority 2 Priority 3 Trait importance 1  \\\n",
+       "Person ID                                                           \n",
+       "1          Assurance  Individuality    Fashion           Openness   \n",
+       "2          Assurance  Individuality    Fashion           Openness   \n",
+       "3          Assurance  Individuality    Fashion           Openness   \n",
+       "4          Assurance  Individuality    Fashion           Openness   \n",
+       "5          Assurance  Individuality    Fashion           Openness   \n",
+       "6          Assurance  Individuality    Fashion           Openness   \n",
+       "7          Assurance  Individuality    Fashion           Openness   \n",
+       "8          Assurance  Individuality    Fashion           Openness   \n",
+       "9          Assurance  Individuality    Fashion           Openness   \n",
+       "10         Assurance  Individuality    Fashion           Openness   \n",
+       "\n",
+       "          Trait importance 2 Trait importance 3  \n",
+       "Person ID                                        \n",
+       "1               Extraversion  Conscientiousness  \n",
+       "2               Extraversion  Conscientiousness  \n",
+       "3               Extraversion  Conscientiousness  \n",
+       "4               Extraversion  Conscientiousness  \n",
+       "5               Extraversion  Conscientiousness  \n",
+       "6               Extraversion  Conscientiousness  \n",
+       "7               Extraversion  Conscientiousness  \n",
+       "8               Extraversion  Conscientiousness  \n",
+       "9               Extraversion  Conscientiousness  \n",
+       "10              Extraversion  Conscientiousness  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._priority_calculation(\n",
+    "    correlation_coefficients = df_clothing_styles,\n",
+    "    col_name_ocean = 'Trait',\n",
+    "    threshold = 0.55,\n",
+    "    number_priority = 3,\n",
+    "    number_importance_traits = 3,\n",
+    "    out = True\n",
+    ")\n",
     "\n",
-    "for curr_files in tets_name_files:\n",
-    "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'clothing_styles_priorities_mupta_ru', out = True)\n",
     "\n",
-    "# Получение прогнозов\n",
-    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
-    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "# Опционно\n",
+    "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = ['OPE', 'CON', 'EXT', 'AGR', 'NNEU']\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "708fcd2b-eb78-4f58-96d2-19298b8c26d9",
+   "metadata": {},
+   "source": [
+    "### `MuPTA` (en)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "1b1f1294-6f09-4827-85c6-75ccc7fbd375",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:29:55</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:29:56</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.59561</td>\n",
+       "      <td>0.542967</td>\n",
+       "      <td>0.440668</td>\n",
+       "      <td>0.589769</td>\n",
+       "      <td>0.515306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661347</td>\n",
+       "      <td>0.673973</td>\n",
+       "      <td>0.603208</td>\n",
+       "      <td>0.64543</td>\n",
+       "      <td>0.6431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.439868</td>\n",
+       "      <td>0.465049</td>\n",
+       "      <td>0.284547</td>\n",
+       "      <td>0.422551</td>\n",
+       "      <td>0.396058</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.47715</td>\n",
+       "      <td>0.502563</td>\n",
+       "      <td>0.373686</td>\n",
+       "      <td>0.441372</td>\n",
+       "      <td>0.424637</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403292</td>\n",
+       "      <td>0.344359</td>\n",
+       "      <td>0.317304</td>\n",
+       "      <td>0.422228</td>\n",
+       "      <td>0.384346</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.581837</td>\n",
+       "      <td>0.562177</td>\n",
+       "      <td>0.504623</td>\n",
+       "      <td>0.602169</td>\n",
+       "      <td>0.522254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510444</td>\n",
+       "      <td>0.448468</td>\n",
+       "      <td>0.425599</td>\n",
+       "      <td>0.451861</td>\n",
+       "      <td>0.447891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.500526</td>\n",
+       "      <td>0.541376</td>\n",
+       "      <td>0.308529</td>\n",
+       "      <td>0.441178</td>\n",
+       "      <td>0.452412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.427677</td>\n",
+       "      <td>0.511355</td>\n",
+       "      <td>0.301078</td>\n",
+       "      <td>0.434281</td>\n",
+       "      <td>0.442301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566414</td>\n",
+       "      <td>0.659169</td>\n",
+       "      <td>0.434059</td>\n",
+       "      <td>0.59122</td>\n",
+       "      <td>0.579172</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path  Openness Conscientiousness Extraversion  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov   0.59561          0.542967     0.440668   \n",
+       "2          speaker_06_center_83.mov  0.661347          0.673973     0.603208   \n",
+       "3          speaker_07_center_83.mov  0.439868          0.465049     0.284547   \n",
+       "4          speaker_10_center_83.mov   0.47715          0.502563     0.373686   \n",
+       "5          speaker_11_center_83.mov  0.403292          0.344359     0.317304   \n",
+       "6          speaker_15_center_83.mov  0.581837          0.562177     0.504623   \n",
+       "7          speaker_19_center_83.mov  0.510444          0.448468     0.425599   \n",
+       "8          speaker_23_center_83.mov  0.500526          0.541376     0.308529   \n",
+       "9          speaker_24_center_83.mov  0.427677          0.511355     0.301078   \n",
+       "10         speaker_27_center_83.mov  0.566414          0.659169     0.434059   \n",
+       "\n",
+       "          Agreeableness Non-Neuroticism  \n",
+       "Person ID                                \n",
+       "1              0.589769        0.515306  \n",
+       "2               0.64543          0.6431  \n",
+       "3              0.422551        0.396058  \n",
+       "4              0.441372        0.424637  \n",
+       "5              0.422228        0.384346  \n",
+       "6              0.602169        0.522254  \n",
+       "7              0.451861        0.447891  \n",
+       "8              0.441178        0.452412  \n",
+       "9              0.434281        0.442301  \n",
+       "10              0.59122        0.579172  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:29:56</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Metrics</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>MAE</th>\n",
+       "      <td>0.1632</td>\n",
+       "      <td>0.1621</td>\n",
+       "      <td>0.176</td>\n",
+       "      <td>0.2589</td>\n",
+       "      <td>0.1122</td>\n",
+       "      <td>0.1745</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Accuracy</th>\n",
+       "      <td>0.8368</td>\n",
+       "      <td>0.8379</td>\n",
+       "      <td>0.824</td>\n",
+       "      <td>0.7411</td>\n",
+       "      <td>0.8878</td>\n",
+       "      <td>0.8255</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
+       "Metrics                                                              \n",
+       "MAE         0.1632             0.1621         0.176         0.2589   \n",
+       "Accuracy    0.8368             0.8379         0.824         0.7411   \n",
+       "\n",
+       "          Non-Neuroticism    Mean  \n",
+       "Metrics                            \n",
+       "MAE                0.1122  0.1745  \n",
+       "Accuracy           0.8878  0.8255  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 18:29:56</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.1745</span>, средняя точность: <span style=\"color:#1776D2\">0.8255</span> ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**--- Время выполнения: 320.737 сек. ---**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import pandas as pd\n",
+    "\n",
+    "# Импорт модуля\n",
+    "from oceanai.modules.lab.build import Run\n",
+    "\n",
+    "# Создание экземпляра класса\n",
+    "_b5 = Run()\n",
+    "\n",
+    "corpus = 'fi'\n",
+    "lang = 'en'\n",
+    "\n",
+    "# Настройка ядра\n",
+    "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
+    "_b5.chunk_size_ = 2000000      # Размер загрузки файла из сети за 1 шаг\n",
+    "\n",
+    "# Формирование аудиомоделей\n",
+    "res_load_model_hc = _b5.load_audio_model_hc()\n",
+    "res_load_model_nn = _b5.load_audio_model_nn()\n",
+    "\n",
+    "# Загрузка весов аудиомоделей\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Формирование видеомоделей\n",
+    "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
+    "res_load_model_deep_fe = _b5.load_video_model_deep_fe()\n",
+    "res_load_model_nn = _b5.load_video_model_nn()\n",
+    "\n",
+    "# Загрузка весов видеомоделей\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
+    "res_load_text_features = _b5.load_text_features()\n",
+    "\n",
+    "# Формирование текстовых моделей \n",
+    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
+    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
+    "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
+    "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
+    "\n",
+    "# Загрузка весов текстовых моделей\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Формирование модели для мультимодального объединения информации\n",
+    "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
+    "\n",
+    "# Загрузка весов модели для мультимодального объединения информации\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
+    "\n",
+    "PATH_TO_DIR = './video_MuPTA/'\n",
+    "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
+    "\n",
+    "_b5.path_to_save_ = PATH_SAVE_VIDEO\n",
+    "\n",
+    "# Загрузка 10 тестовых аудиовидеозаписей из корпуса MuPTA\n",
+    "# URL: https://hci.nw.ru/en/pages/mupta-corpus\n",
+    "domain = 'https://download.sberdisk.ru/download/file/'\n",
+    "tets_name_files = [\n",
+    "    '477995979?token=2cvyk7CS0mHx2MJ&filename=speaker_06_center_83.mov',\n",
+    "    '477995980?token=jGPtBPS69uzFU6Y&filename=speaker_01_center_83.mov',\n",
+    "    '477995967?token=zCaRbNB6ht5wMPq&filename=speaker_11_center_83.mov',\n",
+    "    '477995966?token=B1rbinDYRQKrI3T&filename=speaker_15_center_83.mov',\n",
+    "    '477995978?token=dEpVDtZg1EQiEQ9&filename=speaker_07_center_83.mov',\n",
+    "    '477995961?token=o1hVjw8G45q9L9Z&filename=speaker_19_center_83.mov',\n",
+    "    '477995964?token=5K220Aqf673VHPq&filename=speaker_23_center_83.mov',\n",
+    "    '477995965?token=v1LVD2KT1cU7Lpb&filename=speaker_24_center_83.mov',\n",
+    "    '477995962?token=tmaSGyyWLA6XCy9&filename=speaker_27_center_83.mov',\n",
+    "    '477995963?token=bTpo96qNDPcwGqb&filename=speaker_10_center_83.mov',\n",
+    "]\n",
+    "\n",
+    "for curr_files in tets_name_files:\n",
+    "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
+    "\n",
+    "# Получение прогнозов\n",
+    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
+    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "\n",
+    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
+    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "\n",
+    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7d2dceb-423d-463d-ba89-61603250689a",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "Для прогнозирования потребительских предпочтений в промышленных товарах необходимо знать коэффициенты корреляции, определяющие взаимосвязь между персональными качествами личности человека и предпочтениями в товарах или услугах.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками автомобилей, представленными в статье:\n",
+    "\n",
+    "1) O'Connor P. J. et al. What Drives Consumer Automobile Choice? Investigating Personality Trait Predictors of Vehicle Preference Factors // Personality and Individual Differences. – 2022. – Vol. 184. – pp. 111220.\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3e9151a3-d8bd-4c76-82b2-4ae935ac6ea0",
+   "metadata": {},
+   "source": [
+    "#### Прогнозирование потребительских предпочтений на характеристики атомобиля"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "b38c6569-1558-447a-875d-5735451e8f26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>Performance</th>\n",
+       "      <th>Classic car features</th>\n",
+       "      <th>Luxury additions</th>\n",
+       "      <th>Fashion and attention</th>\n",
+       "      <th>Recreation</th>\n",
+       "      <th>Technology</th>\n",
+       "      <th>Family friendly</th>\n",
+       "      <th>Safe and reliable</th>\n",
+       "      <th>Practical and easy to use</th>\n",
+       "      <th>Economical/low cost</th>\n",
+       "      <th>Basic features</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.020000</td>\n",
+       "      <td>-0.033333</td>\n",
+       "      <td>-0.030000</td>\n",
+       "      <td>-0.050000</td>\n",
+       "      <td>0.033333</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>-0.030000</td>\n",
+       "      <td>0.136667</td>\n",
+       "      <td>0.106667</td>\n",
+       "      <td>0.093333</td>\n",
+       "      <td>0.006667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.013333</td>\n",
+       "      <td>-0.193333</td>\n",
+       "      <td>-0.063333</td>\n",
+       "      <td>-0.096667</td>\n",
+       "      <td>-0.096667</td>\n",
+       "      <td>0.086667</td>\n",
+       "      <td>-0.063333</td>\n",
+       "      <td>0.280000</td>\n",
+       "      <td>0.180000</td>\n",
+       "      <td>0.130000</td>\n",
+       "      <td>0.143333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.133333</td>\n",
+       "      <td>0.060000</td>\n",
+       "      <td>0.106667</td>\n",
+       "      <td>0.123333</td>\n",
+       "      <td>0.126667</td>\n",
+       "      <td>0.120000</td>\n",
+       "      <td>0.090000</td>\n",
+       "      <td>0.136667</td>\n",
+       "      <td>0.043333</td>\n",
+       "      <td>0.073333</td>\n",
+       "      <td>0.050000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>-0.036667</td>\n",
+       "      <td>-0.193333</td>\n",
+       "      <td>-0.133333</td>\n",
+       "      <td>-0.133333</td>\n",
+       "      <td>-0.090000</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>-0.016667</td>\n",
+       "      <td>0.240000</td>\n",
+       "      <td>0.160000</td>\n",
+       "      <td>0.120000</td>\n",
+       "      <td>0.083333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.016667</td>\n",
+       "      <td>-0.006667</td>\n",
+       "      <td>-0.010000</td>\n",
+       "      <td>-0.006667</td>\n",
+       "      <td>-0.033333</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>-0.023333</td>\n",
+       "      <td>0.093333</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>0.046667</td>\n",
+       "      <td>-0.040000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Trait  Performance  Classic car features  Luxury additions  \\\n",
+       "ID                                                                           \n",
+       "1            Openness     0.020000             -0.033333         -0.030000   \n",
+       "2   Conscientiousness     0.013333             -0.193333         -0.063333   \n",
+       "3        Extraversion     0.133333              0.060000          0.106667   \n",
+       "4       Agreeableness    -0.036667             -0.193333         -0.133333   \n",
+       "5     Non-Neuroticism     0.016667             -0.006667         -0.010000   \n",
+       "\n",
+       "    Fashion and attention  Recreation  Technology  Family friendly  \\\n",
+       "ID                                                                   \n",
+       "1               -0.050000    0.033333    0.013333        -0.030000   \n",
+       "2               -0.096667   -0.096667    0.086667        -0.063333   \n",
+       "3                0.123333    0.126667    0.120000         0.090000   \n",
+       "4               -0.133333   -0.090000    0.046667        -0.016667   \n",
+       "5               -0.006667   -0.033333    0.046667        -0.023333   \n",
+       "\n",
+       "    Safe and reliable  Practical and easy to use  Economical/low cost  \\\n",
+       "ID                                                                      \n",
+       "1            0.136667                   0.106667             0.093333   \n",
+       "2            0.280000                   0.180000             0.130000   \n",
+       "3            0.136667                   0.043333             0.073333   \n",
+       "4            0.240000                   0.160000             0.120000   \n",
+       "5            0.093333                   0.046667             0.046667   \n",
+       "\n",
+       "    Basic features  \n",
+       "ID                  \n",
+       "1         0.006667  \n",
+       "2         0.143333  \n",
+       "3         0.050000  \n",
+       "4         0.083333  \n",
+       "5        -0.040000  "
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/478675818?token=EjfLMqOeK8cfnOu&filename=auto_characteristics.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "df_correlation_coefficients = pd.DataFrame(\n",
+    "    df_correlation_coefficients.drop(['Style and performance', 'Safety and practicality'], axis = 1)\n",
+    ")\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "\n",
+    "df_correlation_coefficients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "6d095685-fda4-4943-9a0f-d0463a39798c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Priority 1</th>\n",
+       "      <th>Priority 2</th>\n",
+       "      <th>Priority 3</th>\n",
+       "      <th>Trait importance 1</th>\n",
+       "      <th>Trait importance 2</th>\n",
+       "      <th>Trait importance 3</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
+       "      <td>Recreation</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>Classic car features</td>\n",
+       "      <td>Fashion and attention</td>\n",
+       "      <td>Luxury additions</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>Classic car features</td>\n",
+       "      <td>Fashion and attention</td>\n",
+       "      <td>Luxury additions</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>Classic car features</td>\n",
+       "      <td>Fashion and attention</td>\n",
+       "      <td>Luxury additions</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>Classic car features</td>\n",
+       "      <td>Fashion and attention</td>\n",
+       "      <td>Luxury additions</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>Classic car features</td>\n",
+       "      <td>Fashion and attention</td>\n",
+       "      <td>Luxury additions</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>Classic car features</td>\n",
+       "      <td>Fashion and attention</td>\n",
+       "      <td>Luxury additions</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>Safe and reliable</td>\n",
+       "      <td>Practical and easy to use</td>\n",
+       "      <td>Economical/low cost</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Openness</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
+       "\n",
+       "                          Priority 1                 Priority 2  \\\n",
+       "Person ID                                                         \n",
+       "1          Practical and easy to use        Economical/low cost   \n",
+       "2                  Safe and reliable  Practical and easy to use   \n",
+       "3               Classic car features      Fashion and attention   \n",
+       "4               Classic car features      Fashion and attention   \n",
+       "5               Classic car features      Fashion and attention   \n",
+       "6                  Safe and reliable  Practical and easy to use   \n",
+       "7               Classic car features      Fashion and attention   \n",
+       "8               Classic car features      Fashion and attention   \n",
+       "9               Classic car features      Fashion and attention   \n",
+       "10                 Safe and reliable  Practical and easy to use   \n",
+       "\n",
+       "                    Priority 3 Trait importance 1 Trait importance 2  \\\n",
+       "Person ID                                                              \n",
+       "1                   Recreation           Openness      Agreeableness   \n",
+       "2          Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "3             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "4             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "5             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "6          Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "7             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "8             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "9             Luxury additions      Agreeableness  Conscientiousness   \n",
+       "10         Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "\n",
+       "          Trait importance 3  \n",
+       "Person ID                     \n",
+       "1            Non-Neuroticism  \n",
+       "2                   Openness  \n",
+       "3                   Openness  \n",
+       "4                   Openness  \n",
+       "5                   Openness  \n",
+       "6                   Openness  \n",
+       "7                   Openness  \n",
+       "8                   Openness  \n",
+       "9                   Openness  \n",
+       "10                  Openness  "
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._priority_calculation(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    col_name_ocean = 'Trait',\n",
+    "    threshold = 0.55,\n",
+    "    number_priority = 3,\n",
+    "    number_importance_traits = 3,\n",
+    "    out = False\n",
+    ")\n",
     "\n",
-    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'auto_characteristics_priorities_mupta_en', out = True)\n",
     "\n",
-    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
+    "# Опционно\n",
+    "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = ['OPE', 'CON', 'EXT', 'AGR', 'NNEU']\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "b7d2dceb-423d-463d-ba89-61603250689a",
+   "id": "7343080a-898e-4718-8d44-26f787c6cc24",
    "metadata": {},
    "source": [
-    "<hr>\n",
-    "\n",
-    "Для прогнозирования потребительских предпочтений в промышленных товарах необходимо знать коэффициенты корреляции, определяющие взаимосвязь между персональными качествами личности человека и предпочтениями в товарах или услугах.\n",
-    "\n",
-    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками автомобилей, представленными в статье:\n",
+    "#### Прогнозирование потребительских предпочтений на характеристики мобильного устройства\n",
     "\n",
-    "1) O'Connor P. J. et al. What Drives Consumer Automobile Choice? Investigating Personality Trait Predictors of Vehicle Preference Factors // Personality and Individual Differences. – 2022. – Vol. 184. – pp. 111220.\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками мобильного устройства, представленными в статье:\n",
     "\n",
-    "Пользователь может установить свои коэффициенты корреляции."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3e9151a3-d8bd-4c76-82b2-4ae935ac6ea0",
-   "metadata": {},
-   "source": [
-    "#### Прогнозирование потребительских предпочтений на характеристики атомобиля"
+    "1) Peltonen E., Sharmila P., Asare K. O., Visuri A., Lagerspetz E., Ferreira D. (2020). When phones get personal: Predicting Big Five personality traits from application usage // Pervasive and Mobile Computing. – 2020. – Vol. 69. – 101269."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "id": "b38c6569-1558-447a-875d-5735451e8f26",
+   "execution_count": 19,
+   "id": "bacc7c56-18f4-4575-9f9e-54a038bf5df8",
    "metadata": {},
    "outputs": [
     {
@@ -3417,17 +4725,22 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Trait</th>\n",
-       "      <th>Performance</th>\n",
-       "      <th>Classic car features</th>\n",
-       "      <th>Luxury additions</th>\n",
-       "      <th>Fashion and attention</th>\n",
-       "      <th>Recreation</th>\n",
-       "      <th>Technology</th>\n",
-       "      <th>Family friendly</th>\n",
-       "      <th>Safe and reliable</th>\n",
-       "      <th>Practical and easy to use</th>\n",
-       "      <th>Economical/low cost</th>\n",
-       "      <th>Basic features</th>\n",
+       "      <th>Communication</th>\n",
+       "      <th>Game Action</th>\n",
+       "      <th>Game Board</th>\n",
+       "      <th>Game Casino</th>\n",
+       "      <th>Game Educational</th>\n",
+       "      <th>Game Simulation</th>\n",
+       "      <th>Game Trivia</th>\n",
+       "      <th>Entertainment</th>\n",
+       "      <th>Finance</th>\n",
+       "      <th>Health and Fitness</th>\n",
+       "      <th>Media and Video</th>\n",
+       "      <th>Music and Audio</th>\n",
+       "      <th>News and Magazines</th>\n",
+       "      <th>Personalisation</th>\n",
+       "      <th>Travel and Local</th>\n",
+       "      <th>Weather</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ID</th>\n",
@@ -3443,145 +4756,173 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Openness</td>\n",
-       "      <td>0.020000</td>\n",
-       "      <td>-0.033333</td>\n",
-       "      <td>-0.030000</td>\n",
-       "      <td>-0.050000</td>\n",
-       "      <td>0.033333</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>-0.030000</td>\n",
-       "      <td>0.136667</td>\n",
-       "      <td>0.106667</td>\n",
-       "      <td>0.093333</td>\n",
-       "      <td>0.006667</td>\n",
+       "      <td>0.118</td>\n",
+       "      <td>0.056</td>\n",
+       "      <td>0.079</td>\n",
+       "      <td>0.342</td>\n",
+       "      <td>0.027</td>\n",
+       "      <td>0.104</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>0.013333</td>\n",
-       "      <td>-0.193333</td>\n",
-       "      <td>-0.063333</td>\n",
-       "      <td>-0.096667</td>\n",
-       "      <td>-0.096667</td>\n",
-       "      <td>0.086667</td>\n",
-       "      <td>-0.063333</td>\n",
-       "      <td>0.280000</td>\n",
-       "      <td>0.180000</td>\n",
-       "      <td>0.130000</td>\n",
-       "      <td>0.143333</td>\n",
+       "      <td>0.119</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>0.107</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.039</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>0.119</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Extraversion</td>\n",
-       "      <td>0.133333</td>\n",
-       "      <td>0.060000</td>\n",
-       "      <td>0.106667</td>\n",
-       "      <td>0.123333</td>\n",
-       "      <td>0.126667</td>\n",
-       "      <td>0.120000</td>\n",
-       "      <td>0.090000</td>\n",
-       "      <td>0.136667</td>\n",
-       "      <td>0.043333</td>\n",
-       "      <td>0.073333</td>\n",
-       "      <td>0.050000</td>\n",
+       "      <td>0.246</td>\n",
+       "      <td>0.182</td>\n",
+       "      <td>0.211</td>\n",
+       "      <td>0.311</td>\n",
+       "      <td>0.102</td>\n",
+       "      <td>0.165</td>\n",
+       "      <td>0.223</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>-0.036667</td>\n",
-       "      <td>-0.193333</td>\n",
-       "      <td>-0.133333</td>\n",
-       "      <td>-0.133333</td>\n",
-       "      <td>-0.090000</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>-0.016667</td>\n",
-       "      <td>0.240000</td>\n",
-       "      <td>0.160000</td>\n",
-       "      <td>0.120000</td>\n",
-       "      <td>0.083333</td>\n",
+       "      <td>0.218</td>\n",
+       "      <td>0.104</td>\n",
+       "      <td>0.164</td>\n",
+       "      <td>0.284</td>\n",
+       "      <td>0.165</td>\n",
+       "      <td>0.122</td>\n",
+       "      <td>0.162</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.003</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>Non-Neuroticism</td>\n",
-       "      <td>0.016667</td>\n",
-       "      <td>-0.006667</td>\n",
-       "      <td>-0.010000</td>\n",
-       "      <td>-0.006667</td>\n",
-       "      <td>-0.033333</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>-0.023333</td>\n",
-       "      <td>0.093333</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>0.046667</td>\n",
-       "      <td>-0.040000</td>\n",
+       "      <td>0.046</td>\n",
+       "      <td>0.047</td>\n",
+       "      <td>0.125</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.272</td>\n",
+       "      <td>0.179</td>\n",
+       "      <td>0.214</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.030</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.007</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Trait  Performance  Classic car features  Luxury additions  \\\n",
+       "                Trait  Communication  Game Action  Game Board  Game Casino  \\\n",
        "ID                                                                           \n",
-       "1            Openness     0.020000             -0.033333         -0.030000   \n",
-       "2   Conscientiousness     0.013333             -0.193333         -0.063333   \n",
-       "3        Extraversion     0.133333              0.060000          0.106667   \n",
-       "4       Agreeableness    -0.036667             -0.193333         -0.133333   \n",
-       "5     Non-Neuroticism     0.016667             -0.006667         -0.010000   \n",
+       "1            Openness          0.118        0.056       0.079        0.342   \n",
+       "2   Conscientiousness          0.119        0.043       0.107        0.448   \n",
+       "3        Extraversion          0.246        0.182       0.211        0.311   \n",
+       "4       Agreeableness          0.218        0.104       0.164        0.284   \n",
+       "5     Non-Neuroticism          0.046        0.047       0.125        0.515   \n",
        "\n",
-       "    Fashion and attention  Recreation  Technology  Family friendly  \\\n",
-       "ID                                                                   \n",
-       "1               -0.050000    0.033333    0.013333        -0.030000   \n",
-       "2               -0.096667   -0.096667    0.086667        -0.063333   \n",
-       "3                0.123333    0.126667    0.120000         0.090000   \n",
-       "4               -0.133333   -0.090000    0.046667        -0.016667   \n",
-       "5               -0.006667   -0.033333    0.046667        -0.023333   \n",
+       "    Game Educational  Game Simulation  Game Trivia  Entertainment  Finance  \\\n",
+       "ID                                                                           \n",
+       "1              0.027            0.104        0.026          0.000    0.006   \n",
+       "2              0.039            0.012        0.119          0.000    0.005   \n",
+       "3              0.102            0.165        0.223          0.001    0.003   \n",
+       "4              0.165            0.122        0.162          0.000    0.003   \n",
+       "5              0.272            0.179        0.214          0.002    0.030   \n",
        "\n",
-       "    Safe and reliable  Practical and easy to use  Economical/low cost  \\\n",
-       "ID                                                                      \n",
-       "1            0.136667                   0.106667             0.093333   \n",
-       "2            0.280000                   0.180000             0.130000   \n",
-       "3            0.136667                   0.043333             0.073333   \n",
-       "4            0.240000                   0.160000             0.120000   \n",
-       "5            0.093333                   0.046667             0.046667   \n",
+       "    Health and Fitness  Media and Video  Music and Audio  News and Magazines  \\\n",
+       "ID                                                                             \n",
+       "1                0.002            0.000            0.000               0.001   \n",
+       "2                0.001            0.000            0.002               0.002   \n",
+       "3                0.000            0.001            0.001               0.001   \n",
+       "4                0.001            0.000            0.002               0.002   \n",
+       "5                0.001            0.000            0.005               0.003   \n",
        "\n",
-       "    Basic features  \n",
-       "ID                  \n",
-       "1         0.006667  \n",
-       "2         0.143333  \n",
-       "3         0.050000  \n",
-       "4         0.083333  \n",
-       "5        -0.040000  "
+       "    Personalisation  Travel and Local  Weather  \n",
+       "ID                                              \n",
+       "1             0.004             0.002    0.004  \n",
+       "2             0.001             0.001    0.003  \n",
+       "3             0.004             0.009    0.003  \n",
+       "4             0.001             0.004    0.003  \n",
+       "5             0.008             0.004    0.007  "
       ]
      },
-     "execution_count": 13,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Загрузка датафрейма с коэффициентами корреляции\n",
-    "url = 'https://download.sberdisk.ru/download/file/478675818?token=EjfLMqOeK8cfnOu&filename=auto_characteristics.csv'\n",
-    "df_correlation_coefficients = pd.read_csv(url)\n",
-    "df_correlation_coefficients = pd.DataFrame(\n",
-    "    df_correlation_coefficients.drop(['Style and performance', 'Safety and practicality'], axis = 1)\n",
-    ")\n",
-    "df_correlation_coefficients.index.name = 'ID'\n",
-    "df_correlation_coefficients.index += 1\n",
-    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "url = 'https://download.sberdisk.ru/download/file/478676690?token=7KcAxPqMpWiYQnx&filename=divice_characteristics.csv'\n",
+    "df_divice_characteristics = pd.read_csv(url)\n",
     "\n",
-    "df_correlation_coefficients"
+    "df_divice_characteristics.index.name = 'ID'\n",
+    "df_divice_characteristics.index += 1\n",
+    "df_divice_characteristics.index = df_divice_characteristics.index.map(str)\n",
+    "\n",
+    "df_divice_characteristics"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "id": "6d095685-fda4-4943-9a0f-d0463a39798c",
+   "execution_count": 20,
+   "id": "00356c08-6004-4fe2-b676-61301bebeff6",
    "metadata": {},
    "outputs": [
     {
@@ -3638,14 +4979,14 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Family friendly</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Health and Fitness</td>\n",
+       "      <td>Media and Video</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Openness</td>\n",
        "      <td>Non-Neuroticism</td>\n",
@@ -3653,137 +4994,137 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Trivia</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
-       "      <td>Luxury additions</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>Media and Video</td>\n",
+       "      <td>Entertainment</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
-       "      <td>Luxury additions</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>Media and Video</td>\n",
+       "      <td>Entertainment</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
-       "      <td>Luxury additions</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>Media and Video</td>\n",
+       "      <td>Entertainment</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
-       "      <td>Family friendly</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Communication</td>\n",
+       "      <td>Game Board</td>\n",
        "      <td>Agreeableness</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "      <td>Openness</td>\n",
-       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
-       "      <td>Luxury additions</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>Media and Video</td>\n",
+       "      <td>Entertainment</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
-       "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
-       "      <td>0.434</td>\n",
-       "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
-       "      <td>Luxury additions</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>Media and Video</td>\n",
+       "      <td>Entertainment</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>Classic car features</td>\n",
-       "      <td>Fashion and attention</td>\n",
-       "      <td>Luxury additions</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>Media and Video</td>\n",
+       "      <td>Entertainment</td>\n",
+       "      <td>Health and Fitness</td>\n",
        "      <td>Agreeableness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Openness</td>\n",
+       "      <td>Extraversion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
-       "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>Safe and reliable</td>\n",
-       "      <td>Practical and easy to use</td>\n",
-       "      <td>Economical/low cost</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>Game Casino</td>\n",
+       "      <td>Game Educational</td>\n",
+       "      <td>Game Trivia</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "      <td>Conscientiousness</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -3792,73 +5133,60 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489   \n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621   \n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397   \n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444   \n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355   \n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499   \n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441   \n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434   \n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415   \n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554   \n",
-       "\n",
-       "                          Priority 1                 Priority 2  \\\n",
-       "Person ID                                                         \n",
-       "1          Practical and easy to use        Economical/low cost   \n",
-       "2                  Safe and reliable  Practical and easy to use   \n",
-       "3               Classic car features      Fashion and attention   \n",
-       "4               Classic car features      Fashion and attention   \n",
-       "5               Classic car features      Fashion and attention   \n",
-       "6          Practical and easy to use        Economical/low cost   \n",
-       "7               Classic car features      Fashion and attention   \n",
-       "8               Classic car features      Fashion and attention   \n",
-       "9               Classic car features      Fashion and attention   \n",
-       "10                 Safe and reliable  Practical and easy to use   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
        "\n",
-       "                    Priority 3 Trait importance 1 Trait importance 2  \\\n",
-       "Person ID                                                              \n",
-       "1              Family friendly      Agreeableness           Openness   \n",
-       "2          Economical/low cost  Conscientiousness      Agreeableness   \n",
-       "3             Luxury additions      Agreeableness  Conscientiousness   \n",
-       "4             Luxury additions      Agreeableness  Conscientiousness   \n",
-       "5             Luxury additions      Agreeableness  Conscientiousness   \n",
-       "6              Family friendly      Agreeableness           Openness   \n",
-       "7             Luxury additions      Agreeableness  Conscientiousness   \n",
-       "8             Luxury additions      Agreeableness  Conscientiousness   \n",
-       "9             Luxury additions      Agreeableness  Conscientiousness   \n",
-       "10         Economical/low cost  Conscientiousness      Agreeableness   \n",
+       "                Priority 1          Priority 2          Priority 3  \\\n",
+       "Person ID                                                            \n",
+       "1            Communication  Health and Fitness     Media and Video   \n",
+       "2              Game Casino       Communication         Game Trivia   \n",
+       "3          Media and Video       Entertainment  Health and Fitness   \n",
+       "4          Media and Video       Entertainment  Health and Fitness   \n",
+       "5          Media and Video       Entertainment  Health and Fitness   \n",
+       "6              Game Casino       Communication          Game Board   \n",
+       "7          Media and Video       Entertainment  Health and Fitness   \n",
+       "8          Media and Video       Entertainment  Health and Fitness   \n",
+       "9          Media and Video       Entertainment  Health and Fitness   \n",
+       "10             Game Casino    Game Educational         Game Trivia   \n",
        "\n",
-       "          Trait importance 3  \n",
-       "Person ID                     \n",
-       "1            Non-Neuroticism  \n",
-       "2                   Openness  \n",
-       "3                   Openness  \n",
-       "4                   Openness  \n",
-       "5                   Openness  \n",
-       "6            Non-Neuroticism  \n",
-       "7                   Openness  \n",
-       "8                   Openness  \n",
-       "9                   Openness  \n",
-       "10           Non-Neuroticism  "
+       "          Trait importance 1 Trait importance 2 Trait importance 3  \n",
+       "Person ID                                                           \n",
+       "1              Agreeableness           Openness    Non-Neuroticism  \n",
+       "2            Non-Neuroticism       Extraversion  Conscientiousness  \n",
+       "3              Agreeableness  Conscientiousness       Extraversion  \n",
+       "4              Agreeableness  Conscientiousness       Extraversion  \n",
+       "5          Conscientiousness      Agreeableness       Extraversion  \n",
+       "6              Agreeableness  Conscientiousness           Openness  \n",
+       "7          Conscientiousness      Agreeableness       Extraversion  \n",
+       "8              Agreeableness  Conscientiousness       Extraversion  \n",
+       "9              Agreeableness  Conscientiousness       Extraversion  \n",
+       "10           Non-Neuroticism  Conscientiousness      Agreeableness  "
       ]
      },
-     "execution_count": 14,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_b5._priority_calculation(\n",
-    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    correlation_coefficients = df_divice_characteristics,\n",
     "    col_name_ocean = 'Trait',\n",
     "    threshold = 0.55,\n",
     "    number_priority = 3,\n",
     "    number_importance_traits = 3,\n",
-    "    out = False\n",
+    "    out = True\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_priority_, name = 'auto_characteristics_priorities_mupta_en', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'divice_characteristics_priorities_mupta_en', out = True)\n",
     "\n",
     "# Опционно\n",
     "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
@@ -3869,20 +5197,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7343080a-898e-4718-8d44-26f787c6cc24",
+   "id": "fb6b2c81",
    "metadata": {},
    "source": [
-    "#### Прогнозирование потребительских предпочтений на характеристики мобильного устройства\n",
+    "#### Прогнозирование потребительских предпочтений по стилю одежды\n",
     "\n",
-    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и характеристиками мобильного устройства, представленными в статье:\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами человека и стилем одежды, представленными в статье:\n",
     "\n",
-    "1) Peltonen E., Sharmila P., Asare K. O., Visuri A., Lagerspetz E., Ferreira D. (2020). When phones get personal: Predicting Big Five personality traits from application usage // Pervasive and Mobile Computing. – 2020. – Vol. 69. – 101269."
+    "1) Stolovy T. Styling the self: clothing practices, personality traits, and body image among Israeli women // Frontiers in psychology. - 2022. - vol. 12. - 719318."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "bacc7c56-18f4-4575-9f9e-54a038bf5df8",
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "485acc90",
    "metadata": {},
    "outputs": [
     {
@@ -3907,22 +5235,11 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Trait</th>\n",
-       "      <th>Communication</th>\n",
-       "      <th>Game Action</th>\n",
-       "      <th>Game Board</th>\n",
-       "      <th>Game Casino</th>\n",
-       "      <th>Game Educational</th>\n",
-       "      <th>Game Simulation</th>\n",
-       "      <th>Game Trivia</th>\n",
-       "      <th>Entertainment</th>\n",
-       "      <th>Finance</th>\n",
-       "      <th>Health and Fitness</th>\n",
-       "      <th>Media and Video</th>\n",
-       "      <th>Music and Audio</th>\n",
-       "      <th>News and Magazines</th>\n",
-       "      <th>Personalisation</th>\n",
-       "      <th>Travel and Local</th>\n",
-       "      <th>Weather</th>\n",
+       "      <th>Comfort</th>\n",
+       "      <th>Camouflage</th>\n",
+       "      <th>Assurance</th>\n",
+       "      <th>Fashion</th>\n",
+       "      <th>Individuality</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ID</th>\n",
@@ -3932,179 +5249,89 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Openness</td>\n",
-       "      <td>0.118</td>\n",
-       "      <td>0.056</td>\n",
-       "      <td>0.079</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.027</td>\n",
-       "      <td>0.104</td>\n",
-       "      <td>0.026</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.006</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.004</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.24</td>\n",
+       "      <td>0.31</td>\n",
+       "      <td>0.07</td>\n",
+       "      <td>0.31</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>0.119</td>\n",
-       "      <td>0.043</td>\n",
-       "      <td>0.107</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>0.039</td>\n",
-       "      <td>0.012</td>\n",
-       "      <td>0.119</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.005</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.24</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.15</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Extraversion</td>\n",
-       "      <td>0.246</td>\n",
-       "      <td>0.182</td>\n",
-       "      <td>0.211</td>\n",
-       "      <td>0.311</td>\n",
-       "      <td>0.102</td>\n",
-       "      <td>0.165</td>\n",
-       "      <td>0.223</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.009</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>-0.01</td>\n",
+       "      <td>-0.19</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.13</td>\n",
+       "      <td>0.14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>0.218</td>\n",
-       "      <td>0.104</td>\n",
-       "      <td>0.164</td>\n",
-       "      <td>0.284</td>\n",
-       "      <td>0.165</td>\n",
-       "      <td>0.122</td>\n",
-       "      <td>0.162</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>-0.16</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>-0.09</td>\n",
+       "      <td>-0.05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>Non-Neuroticism</td>\n",
-       "      <td>0.046</td>\n",
-       "      <td>0.047</td>\n",
-       "      <td>0.125</td>\n",
-       "      <td>0.515</td>\n",
-       "      <td>0.272</td>\n",
-       "      <td>0.179</td>\n",
-       "      <td>0.214</td>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.030</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.005</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.008</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.007</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>-0.16</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.06</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                Trait  Communication  Game Action  Game Board  Game Casino  \\\n",
-       "ID                                                                           \n",
-       "1            Openness          0.118        0.056       0.079        0.342   \n",
-       "2   Conscientiousness          0.119        0.043       0.107        0.448   \n",
-       "3        Extraversion          0.246        0.182       0.211        0.311   \n",
-       "4       Agreeableness          0.218        0.104       0.164        0.284   \n",
-       "5     Non-Neuroticism          0.046        0.047       0.125        0.515   \n",
-       "\n",
-       "    Game Educational  Game Simulation  Game Trivia  Entertainment  Finance  \\\n",
+       "                Trait  Comfort  Camouflage  Assurance  Fashion  Individuality\n",
        "ID                                                                           \n",
-       "1              0.027            0.104        0.026          0.000    0.006   \n",
-       "2              0.039            0.012        0.119          0.000    0.005   \n",
-       "3              0.102            0.165        0.223          0.001    0.003   \n",
-       "4              0.165            0.122        0.162          0.000    0.003   \n",
-       "5              0.272            0.179        0.214          0.002    0.030   \n",
-       "\n",
-       "    Health and Fitness  Media and Video  Music and Audio  News and Magazines  \\\n",
-       "ID                                                                             \n",
-       "1                0.002            0.000            0.000               0.001   \n",
-       "2                0.001            0.000            0.002               0.002   \n",
-       "3                0.000            0.001            0.001               0.001   \n",
-       "4                0.001            0.000            0.002               0.002   \n",
-       "5                0.001            0.000            0.005               0.003   \n",
-       "\n",
-       "    Personalisation  Travel and Local  Weather  \n",
-       "ID                                              \n",
-       "1             0.004             0.002    0.004  \n",
-       "2             0.001             0.001    0.003  \n",
-       "3             0.004             0.009    0.003  \n",
-       "4             0.001             0.004    0.003  \n",
-       "5             0.008             0.004    0.007  "
+       "1            Openness     0.01       -0.24       0.31     0.07           0.31\n",
+       "2   Conscientiousness    -0.03       -0.24       0.17     0.09           0.15\n",
+       "3        Extraversion    -0.01       -0.19       0.30     0.13           0.14\n",
+       "4       Agreeableness     0.16       -0.16       0.15    -0.09          -0.05\n",
+       "5     Non-Neuroticism     0.03       -0.16       0.01     0.00           0.06"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Загрузка датафрейма с коэффициентами корреляции\n",
-    "url = 'https://download.sberdisk.ru/download/file/478676690?token=7KcAxPqMpWiYQnx&filename=divice_characteristics.csv'\n",
-    "df_divice_characteristics = pd.read_csv(url)\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644097?token=KGtSGMxjZtWXmBz&filename=df_%D1%81lothing_style_correlation.csv'\n",
+    "df_clothing_styles = pd.read_csv(url)\n",
     "\n",
-    "df_divice_characteristics.index.name = 'ID'\n",
-    "df_divice_characteristics.index += 1\n",
-    "df_divice_characteristics.index = df_divice_characteristics.index.map(str)\n",
+    "df_clothing_styles.index.name = 'ID'\n",
+    "df_clothing_styles.index += 1\n",
+    "df_clothing_styles.index = df_clothing_styles.index.map(str)\n",
     "\n",
-    "df_divice_characteristics"
+    "df_clothing_styles"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "id": "00356c08-6004-4fe2-b676-61301bebeff6",
+   "execution_count": 22,
+   "id": "1ca93f2e",
    "metadata": {},
    "outputs": [
     {
@@ -4161,150 +5388,150 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Health and Fitness</td>\n",
-       "      <td>Media and Video</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Assurance</td>\n",
        "      <td>Agreeableness</td>\n",
-       "      <td>Openness</td>\n",
        "      <td>Non-Neuroticism</td>\n",
+       "      <td>Conscientiousness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Communication</td>\n",
-       "      <td>Game Trivia</td>\n",
-       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
        "      <td>Extraversion</td>\n",
        "      <td>Conscientiousness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Fashion</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Fashion</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Openness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>Health and Fitness</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>News and Magazines</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Comfort</td>\n",
        "      <td>Openness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>Agreeableness</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Fashion</td>\n",
+       "      <td>Openness</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Agreeableness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
-       "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
-       "      <td>0.434</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Fashion</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>Media and Video</td>\n",
-       "      <td>Entertainment</td>\n",
-       "      <td>Health and Fitness</td>\n",
-       "      <td>Agreeableness</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>Camouflage</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Fashion</td>\n",
        "      <td>Conscientiousness</td>\n",
-       "      <td>Extraversion</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
-       "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>Game Casino</td>\n",
-       "      <td>Game Educational</td>\n",
-       "      <td>Game Trivia</td>\n",
-       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>Assurance</td>\n",
+       "      <td>Individuality</td>\n",
+       "      <td>Comfort</td>\n",
+       "      <td>Openness</td>\n",
        "      <td>Conscientiousness</td>\n",
        "      <td>Agreeableness</td>\n",
        "    </tr>\n",
@@ -4315,52 +5542,52 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
        "Person ID                                                                \n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489   \n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621   \n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397   \n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444   \n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355   \n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499   \n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441   \n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434   \n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415   \n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
        "\n",
-       "                   Priority 1          Priority 2          Priority 3  \\\n",
-       "Person ID                                                               \n",
-       "1               Communication  Health and Fitness     Media and Video   \n",
-       "2                 Game Casino       Communication         Game Trivia   \n",
-       "3             Media and Video       Entertainment  Health and Fitness   \n",
-       "4             Media and Video       Entertainment  Health and Fitness   \n",
-       "5             Media and Video       Entertainment  Health and Fitness   \n",
-       "6          Health and Fitness     Media and Video  News and Magazines   \n",
-       "7             Media and Video       Entertainment  Health and Fitness   \n",
-       "8             Media and Video       Entertainment  Health and Fitness   \n",
-       "9             Media and Video       Entertainment  Health and Fitness   \n",
-       "10                Game Casino    Game Educational         Game Trivia   \n",
+       "           Priority 1     Priority 2 Priority 3 Trait importance 1  \\\n",
+       "Person ID                                                            \n",
+       "1             Comfort     Camouflage  Assurance      Agreeableness   \n",
+       "2           Assurance  Individuality    Fashion           Openness   \n",
+       "3          Camouflage        Comfort    Fashion  Conscientiousness   \n",
+       "4          Camouflage        Comfort    Fashion  Conscientiousness   \n",
+       "5          Camouflage        Fashion    Comfort           Openness   \n",
+       "6           Assurance  Individuality    Comfort           Openness   \n",
+       "7          Camouflage        Comfort    Fashion           Openness   \n",
+       "8          Camouflage        Comfort    Fashion  Conscientiousness   \n",
+       "9          Camouflage        Comfort    Fashion  Conscientiousness   \n",
+       "10          Assurance  Individuality    Comfort           Openness   \n",
        "\n",
-       "          Trait importance 1 Trait importance 2 Trait importance 3  \n",
-       "Person ID                                                           \n",
-       "1              Agreeableness           Openness    Non-Neuroticism  \n",
-       "2            Non-Neuroticism       Extraversion  Conscientiousness  \n",
-       "3              Agreeableness  Conscientiousness       Extraversion  \n",
-       "4              Agreeableness  Conscientiousness       Extraversion  \n",
-       "5          Conscientiousness      Agreeableness       Extraversion  \n",
-       "6              Agreeableness           Openness       Extraversion  \n",
-       "7          Conscientiousness      Agreeableness       Extraversion  \n",
-       "8              Agreeableness  Conscientiousness       Extraversion  \n",
-       "9              Agreeableness  Conscientiousness       Extraversion  \n",
-       "10           Non-Neuroticism  Conscientiousness      Agreeableness  "
+       "          Trait importance 2 Trait importance 3  \n",
+       "Person ID                                        \n",
+       "1            Non-Neuroticism  Conscientiousness  \n",
+       "2               Extraversion  Conscientiousness  \n",
+       "3                   Openness    Non-Neuroticism  \n",
+       "4                   Openness    Non-Neuroticism  \n",
+       "5          Conscientiousness    Non-Neuroticism  \n",
+       "6          Conscientiousness      Agreeableness  \n",
+       "7          Conscientiousness    Non-Neuroticism  \n",
+       "8                   Openness    Non-Neuroticism  \n",
+       "9                   Openness    Non-Neuroticism  \n",
+       "10         Conscientiousness      Agreeableness  "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "_b5._priority_calculation(\n",
-    "    correlation_coefficients = df_divice_characteristics,\n",
+    "    correlation_coefficients = df_clothing_styles,\n",
     "    col_name_ocean = 'Trait',\n",
     "    threshold = 0.55,\n",
     "    number_priority = 3,\n",
@@ -4368,7 +5595,7 @@
     "    out = True\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_priority_, name = 'divice_characteristics_priorities_mupta_en', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_priority_, name = 'clothing_styles_priorities_mupta_en', out = True)\n",
     "\n",
     "# Опционно\n",
     "df = _b5.df_files_priority_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
@@ -4394,7 +5621,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.11"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/user_guide/notebooks/Pipeline_practical_task_3.ipynb b/docs/source/user_guide/notebooks/Pipeline_practical_task_3.ipynb
index 57b9d56..c528938 100644
--- a/docs/source/user_guide/notebooks/Pipeline_practical_task_3.ipynb
+++ b/docs/source/user_guide/notebooks/Pipeline_practical_task_3.ipynb
@@ -60,7 +60,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:24:17</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:44:08</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -72,7 +72,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:24:19</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_FI\\test\\_plk5k7PBEg.003.mp4 ...</span></p>"
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:44:08</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_FI\\test\\_plk5k7PBEg.003.mp4 ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -123,92 +123,92 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581159</td>\n",
-       "      <td>0.628822</td>\n",
-       "      <td>0.466609</td>\n",
-       "      <td>0.622129</td>\n",
-       "      <td>0.553832</td>\n",
+       "      <td>0.618917</td>\n",
+       "      <td>0.660694</td>\n",
+       "      <td>0.477656</td>\n",
+       "      <td>0.654437</td>\n",
+       "      <td>0.601256</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.463991</td>\n",
-       "      <td>0.418851</td>\n",
-       "      <td>0.41301</td>\n",
-       "      <td>0.493329</td>\n",
-       "      <td>0.423093</td>\n",
+       "      <td>0.461732</td>\n",
+       "      <td>0.413451</td>\n",
+       "      <td>0.415706</td>\n",
+       "      <td>0.498301</td>\n",
+       "      <td>0.431224</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
-       "      <td>0.454281</td>\n",
-       "      <td>0.415049</td>\n",
-       "      <td>0.39189</td>\n",
-       "      <td>0.485114</td>\n",
-       "      <td>0.420741</td>\n",
+       "      <td>0.468002</td>\n",
+       "      <td>0.448618</td>\n",
+       "      <td>0.371742</td>\n",
+       "      <td>0.509602</td>\n",
+       "      <td>0.453739</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588461</td>\n",
-       "      <td>0.643233</td>\n",
-       "      <td>0.530789</td>\n",
-       "      <td>0.603038</td>\n",
-       "      <td>0.593398</td>\n",
+       "      <td>0.585348</td>\n",
+       "      <td>0.616446</td>\n",
+       "      <td>0.49443</td>\n",
+       "      <td>0.605614</td>\n",
+       "      <td>0.587017</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633433</td>\n",
-       "      <td>0.533295</td>\n",
-       "      <td>0.523742</td>\n",
-       "      <td>0.608591</td>\n",
-       "      <td>0.588456</td>\n",
+       "      <td>0.680991</td>\n",
+       "      <td>0.56602</td>\n",
+       "      <td>0.553915</td>\n",
+       "      <td>0.646545</td>\n",
+       "      <td>0.64246</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.636944</td>\n",
-       "      <td>0.542386</td>\n",
-       "      <td>0.558461</td>\n",
-       "      <td>0.570975</td>\n",
-       "      <td>0.558983</td>\n",
+       "      <td>0.66342</td>\n",
+       "      <td>0.551018</td>\n",
+       "      <td>0.557912</td>\n",
+       "      <td>0.585238</td>\n",
+       "      <td>0.587174</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
-       "      <td>0.531518</td>\n",
-       "      <td>0.376987</td>\n",
-       "      <td>0.393309</td>\n",
-       "      <td>0.4904</td>\n",
-       "      <td>0.447881</td>\n",
+       "      <td>0.590237</td>\n",
+       "      <td>0.399273</td>\n",
+       "      <td>0.409554</td>\n",
+       "      <td>0.531861</td>\n",
+       "      <td>0.507134</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610342</td>\n",
-       "      <td>0.541418</td>\n",
-       "      <td>0.563163</td>\n",
-       "      <td>0.595013</td>\n",
-       "      <td>0.569461</td>\n",
+       "      <td>0.60577</td>\n",
+       "      <td>0.523617</td>\n",
+       "      <td>0.531137</td>\n",
+       "      <td>0.594406</td>\n",
+       "      <td>0.57984</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.495809</td>\n",
-       "      <td>0.458526</td>\n",
-       "      <td>0.414436</td>\n",
-       "      <td>0.469152</td>\n",
-       "      <td>0.435461</td>\n",
+       "      <td>0.511002</td>\n",
+       "      <td>0.464702</td>\n",
+       "      <td>0.390882</td>\n",
+       "      <td>0.443663</td>\n",
+       "      <td>0.438811</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.60707</td>\n",
-       "      <td>0.591893</td>\n",
-       "      <td>0.520662</td>\n",
-       "      <td>0.603938</td>\n",
-       "      <td>0.565726</td>\n",
+       "      <td>0.647606</td>\n",
+       "      <td>0.610466</td>\n",
+       "      <td>0.524718</td>\n",
+       "      <td>0.61428</td>\n",
+       "      <td>0.606428</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -217,29 +217,29 @@
       "text/plain": [
        "                          Path  Openness Conscientiousness Extraversion  \\\n",
        "Person ID                                                                 \n",
-       "1          2d6btbaNdfo.000.mp4  0.581159          0.628822     0.466609   \n",
-       "2          300gK3CnzW0.001.mp4  0.463991          0.418851      0.41301   \n",
-       "3          300gK3CnzW0.003.mp4  0.454281          0.415049      0.39189   \n",
-       "4          4vdJGgZpj4k.003.mp4  0.588461          0.643233     0.530789   \n",
-       "5          be0DQawtVkE.002.mp4  0.633433          0.533295     0.523742   \n",
-       "6          cLaZxEf1nE4.004.mp4  0.636944          0.542386     0.558461   \n",
-       "7          g24JGYuT74A.004.mp4  0.531518          0.376987     0.393309   \n",
-       "8          JZNMxa3OKHY.000.mp4  0.610342          0.541418     0.563163   \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.495809          0.458526     0.414436   \n",
-       "10         _plk5k7PBEg.003.mp4   0.60707          0.591893     0.520662   \n",
+       "1          2d6btbaNdfo.000.mp4  0.618917          0.660694     0.477656   \n",
+       "2          300gK3CnzW0.001.mp4  0.461732          0.413451     0.415706   \n",
+       "3          300gK3CnzW0.003.mp4  0.468002          0.448618     0.371742   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585348          0.616446      0.49443   \n",
+       "5          be0DQawtVkE.002.mp4  0.680991           0.56602     0.553915   \n",
+       "6          cLaZxEf1nE4.004.mp4   0.66342          0.551018     0.557912   \n",
+       "7          g24JGYuT74A.004.mp4  0.590237          0.399273     0.409554   \n",
+       "8          JZNMxa3OKHY.000.mp4   0.60577          0.523617     0.531137   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511002          0.464702     0.390882   \n",
+       "10         _plk5k7PBEg.003.mp4  0.647606          0.610466     0.524718   \n",
        "\n",
        "          Agreeableness Non-Neuroticism  \n",
        "Person ID                                \n",
-       "1              0.622129        0.553832  \n",
-       "2              0.493329        0.423093  \n",
-       "3              0.485114        0.420741  \n",
-       "4              0.603038        0.593398  \n",
-       "5              0.608591        0.588456  \n",
-       "6              0.570975        0.558983  \n",
-       "7                0.4904        0.447881  \n",
-       "8              0.595013        0.569461  \n",
-       "9              0.469152        0.435461  \n",
-       "10             0.603938        0.565726  "
+       "1              0.654437        0.601256  \n",
+       "2              0.498301        0.431224  \n",
+       "3              0.509602        0.453739  \n",
+       "4              0.605614        0.587017  \n",
+       "5              0.646545         0.64246  \n",
+       "6              0.585238        0.587174  \n",
+       "7              0.531861        0.507134  \n",
+       "8              0.594406         0.57984  \n",
+       "9              0.443663        0.438811  \n",
+       "10              0.61428        0.606428  "
       ]
      },
      "metadata": {},
@@ -248,7 +248,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:24:19</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:44:08</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -298,21 +298,21 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MAE</th>\n",
-       "      <td>0.0589</td>\n",
-       "      <td>0.0612</td>\n",
-       "      <td>0.0864</td>\n",
-       "      <td>0.0697</td>\n",
-       "      <td>0.0582</td>\n",
-       "      <td>0.0669</td>\n",
+       "      <td>0.0735</td>\n",
+       "      <td>0.0631</td>\n",
+       "      <td>0.0914</td>\n",
+       "      <td>0.0706</td>\n",
+       "      <td>0.0691</td>\n",
+       "      <td>0.0735</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.9411</td>\n",
-       "      <td>0.9388</td>\n",
-       "      <td>0.9136</td>\n",
-       "      <td>0.9303</td>\n",
-       "      <td>0.9418</td>\n",
-       "      <td>0.9331</td>\n",
+       "      <td>0.9265</td>\n",
+       "      <td>0.9369</td>\n",
+       "      <td>0.9086</td>\n",
+       "      <td>0.9294</td>\n",
+       "      <td>0.9309</td>\n",
+       "      <td>0.9265</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -321,13 +321,13 @@
       "text/plain": [
        "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
        "Metrics                                                              \n",
-       "MAE         0.0589             0.0612        0.0864         0.0697   \n",
-       "Accuracy    0.9411             0.9388        0.9136         0.9303   \n",
+       "MAE         0.0735             0.0631        0.0914         0.0706   \n",
+       "Accuracy    0.9265             0.9369        0.9086         0.9294   \n",
        "\n",
        "          Non-Neuroticism    Mean  \n",
        "Metrics                            \n",
-       "MAE                0.0582  0.0669  \n",
-       "Accuracy           0.9418  0.9331  "
+       "MAE                0.0691  0.0735  \n",
+       "Accuracy           0.9309  0.9265  "
       ]
      },
      "metadata": {},
@@ -336,7 +336,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:24:19</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0669</span>, средняя точность: <span style=\"color:#1776D2\">0.9331</span> ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:44:08</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0735</span>, средняя точность: <span style=\"color:#1776D2\">0.9265</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -360,7 +360,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 67.109 сек. ---**</span>"
+       "<span style=\"color:#666\">**--- Время выполнения: 35.328 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -402,11 +402,11 @@
     "res_load_model_nn = _b5.load_audio_model_nn()\n",
     "\n",
     "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование видеомоделей\n",
     "res_load_model_hc = _b5.load_video_model_hc(lang='en')\n",
@@ -414,14 +414,14 @@
     "res_load_model_nn = _b5.load_video_model_nn()\n",
     "\n",
     "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
     "res_load_text_features = _b5.load_text_features()\n",
@@ -433,18 +433,18 @@
     "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
     "\n",
     "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование модели для мультимодального объединения информации\n",
     "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
     "\n",
     "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
     "\n",
     "PATH_TO_DIR = './video_FI/'\n",
     "PATH_SAVE_VIDEO = './video_FI/test/'\n",
@@ -475,7 +475,7 @@
     "_b5.ext_ = ['.mp4'] # Расширения искомых файлов\n",
     "\n",
     "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_[corpus]['sberdisk']\n",
+    "url_accuracy = _b5.true_traits_[corpus]['googledisk']\n",
     "\n",
     "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = 'en')"
    ]
@@ -651,104 +651,104 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.454</td>\n",
+       "      <td>0.023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
        "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>0.078</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.001</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>0.006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>-0.002</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>0.002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.002</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>-0.007</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>-0.002</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>-0.008</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>-0.005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
-       "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
-       "      <td>-0.013</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>-0.008</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>-0.014</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>300gK3CnzW0.003.mp4</td>\n",
-       "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
-       "      <td>-0.154</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>-0.011</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
+       "      <td>0.462</td>\n",
        "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
        "      <td>-0.154</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
-       "      <td>-0.168</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>-0.176</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -757,16 +757,16 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  Match\n",
        "Person ID                                                               \n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448  0.078\n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593  0.001\n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554 -0.002\n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566 -0.007\n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588 -0.008\n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569 -0.013\n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559 -0.014\n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421 -0.154\n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423 -0.154\n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435 -0.168"
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454  0.023\n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507  0.006\n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601  0.002\n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587  0.002\n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606 -0.002\n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642 -0.005\n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580 -0.008\n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587 -0.011\n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431 -0.154\n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439 -0.176"
       ]
      },
      "execution_count": 4,
@@ -853,102 +853,102 @@
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
-       "      <td>0.496</td>\n",
-       "      <td>0.459</td>\n",
-       "      <td>0.414</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.435</td>\n",
-       "      <td>-0.009</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>-0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>-0.012</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
        "      <td>0.454</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.485</td>\n",
-       "      <td>0.421</td>\n",
-       "      <td>-0.010</td>\n",
+       "      <td>-0.193</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>300gK3CnzW0.001.mp4</td>\n",
-       "      <td>0.464</td>\n",
-       "      <td>0.419</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.423</td>\n",
-       "      <td>-0.013</td>\n",
+       "      <th>7</th>\n",
+       "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
+       "      <td>0.532</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>-0.205</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>JZNMxa3OKHY.000.mp4</td>\n",
-       "      <td>0.610</td>\n",
-       "      <td>0.541</td>\n",
-       "      <td>0.563</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.569</td>\n",
-       "      <td>-0.207</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>-0.209</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>-0.219</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>cLaZxEf1nE4.004.mp4</td>\n",
-       "      <td>0.637</td>\n",
-       "      <td>0.542</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
        "      <td>0.558</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>-0.211</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2d6btbaNdfo.000.mp4</td>\n",
-       "      <td>0.581</td>\n",
-       "      <td>0.629</td>\n",
-       "      <td>0.467</td>\n",
-       "      <td>0.622</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>-0.213</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>-0.222</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>_plk5k7PBEg.003.mp4</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.521</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>-0.213</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>be0DQawtVkE.002.mp4</td>\n",
-       "      <td>0.633</td>\n",
-       "      <td>0.533</td>\n",
-       "      <td>0.524</td>\n",
-       "      <td>0.609</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>-0.216</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>-0.231</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
-       "      <td>0.588</td>\n",
-       "      <td>0.643</td>\n",
-       "      <td>0.531</td>\n",
-       "      <td>0.603</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>-0.221</td>\n",
+       "      <th>1</th>\n",
+       "      <td>2d6btbaNdfo.000.mp4</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>-0.231</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>g24JGYuT74A.004.mp4</td>\n",
-       "      <td>0.532</td>\n",
-       "      <td>0.377</td>\n",
-       "      <td>0.393</td>\n",
-       "      <td>0.490</td>\n",
-       "      <td>0.448</td>\n",
-       "      <td>-0.259</td>\n",
+       "      <th>5</th>\n",
+       "      <td>be0DQawtVkE.002.mp4</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>-0.236</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -957,16 +957,16 @@
       "text/plain": [
        "                          Path    OPE    CON    EXT    AGR   NNEU  Match\n",
        "Person ID                                                               \n",
-       "9          nvlqJbHk_Lc.003.mp4  0.496  0.459  0.414  0.469  0.435 -0.009\n",
-       "3          300gK3CnzW0.003.mp4  0.454  0.415  0.392  0.485  0.421 -0.010\n",
-       "2          300gK3CnzW0.001.mp4  0.464  0.419  0.413  0.493  0.423 -0.013\n",
-       "8          JZNMxa3OKHY.000.mp4  0.610  0.541  0.563  0.595  0.569 -0.207\n",
-       "6          cLaZxEf1nE4.004.mp4  0.637  0.542  0.558  0.571  0.559 -0.211\n",
-       "1          2d6btbaNdfo.000.mp4  0.581  0.629  0.467  0.622  0.554 -0.213\n",
-       "10         _plk5k7PBEg.003.mp4  0.607  0.592  0.521  0.604  0.566 -0.213\n",
-       "5          be0DQawtVkE.002.mp4  0.633  0.533  0.524  0.609  0.588 -0.216\n",
-       "4          4vdJGgZpj4k.003.mp4  0.588  0.643  0.531  0.603  0.593 -0.221\n",
-       "7          g24JGYuT74A.004.mp4  0.532  0.377  0.393  0.490  0.448 -0.259"
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439 -0.004\n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431 -0.012\n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454 -0.193\n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507 -0.205\n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580 -0.209\n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587 -0.219\n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587 -0.222\n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606 -0.231\n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601 -0.231\n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642 -0.236"
       ]
      },
      "execution_count": 5,
@@ -997,42 +997,26 @@
   },
   {
    "cell_type": "markdown",
-   "id": "180a973a-c4ff-43d0-89ef-a809cd6ac00b",
+   "id": "7f218cd2",
    "metadata": {},
    "source": [
-    "### `MuPTA` (ru)"
+    "<hr>\n",
+    "\n",
+    "Для поиска подходящего коллеги по типу личности MBTI необходимо знать коэффициенты корреляции между личностными качествами человека и типами личности MBTI, а также оценки этих качеств для целевого человека.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции, представленных в статье:\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "69c7845d-be20-4632-bd83-bbbf9d47f0f0",
+   "id": "76203e38",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:32:56</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:33:00</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/html": [
@@ -1054,16 +1038,14 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
-       "      <th></th>\n",
+       "      <th>ID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -1074,141 +1056,81 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758137</td>\n",
-       "      <td>0.693356</td>\n",
-       "      <td>0.650108</td>\n",
-       "      <td>0.744589</td>\n",
-       "      <td>0.488671</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.14</td>\n",
+       "      <td>-0.16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.681602</td>\n",
-       "      <td>0.654339</td>\n",
-       "      <td>0.607156</td>\n",
-       "      <td>0.731282</td>\n",
-       "      <td>0.417908</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>-0.04</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666104</td>\n",
-       "      <td>0.656836</td>\n",
-       "      <td>0.567863</td>\n",
-       "      <td>0.685067</td>\n",
-       "      <td>0.378102</td>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.07</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694171</td>\n",
-       "      <td>0.596195</td>\n",
-       "      <td>0.571414</td>\n",
-       "      <td>0.66223</td>\n",
-       "      <td>0.348639</td>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>-0.35</td>\n",
+       "      <td>0.03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.712885</td>\n",
-       "      <td>0.594764</td>\n",
-       "      <td>0.571709</td>\n",
-       "      <td>0.716696</td>\n",
-       "      <td>0.37802</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664158</td>\n",
-       "      <td>0.670411</td>\n",
-       "      <td>0.60421</td>\n",
-       "      <td>0.696056</td>\n",
-       "      <td>0.399842</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761213</td>\n",
-       "      <td>0.652635</td>\n",
-       "      <td>0.651028</td>\n",
-       "      <td>0.788677</td>\n",
-       "      <td>0.459676</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.692788</td>\n",
-       "      <td>0.68324</td>\n",
-       "      <td>0.616737</td>\n",
-       "      <td>0.795205</td>\n",
-       "      <td>0.447242</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.705923</td>\n",
-       "      <td>0.658382</td>\n",
-       "      <td>0.610645</td>\n",
-       "      <td>0.697415</td>\n",
-       "      <td>0.411988</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753417</td>\n",
-       "      <td>0.708372</td>\n",
-       "      <td>0.654608</td>\n",
-       "      <td>0.816416</td>\n",
-       "      <td>0.504743</td>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path  Openness Conscientiousness Extraversion  \\\n",
-       "Person ID                                                                      \n",
-       "1          speaker_01_center_83.mov  0.758137          0.693356     0.650108   \n",
-       "2          speaker_06_center_83.mov  0.681602          0.654339     0.607156   \n",
-       "3          speaker_07_center_83.mov  0.666104          0.656836     0.567863   \n",
-       "4          speaker_10_center_83.mov  0.694171          0.596195     0.571414   \n",
-       "5          speaker_11_center_83.mov  0.712885          0.594764     0.571709   \n",
-       "6          speaker_15_center_83.mov  0.664158          0.670411      0.60421   \n",
-       "7          speaker_19_center_83.mov  0.761213          0.652635     0.651028   \n",
-       "8          speaker_23_center_83.mov  0.692788           0.68324     0.616737   \n",
-       "9          speaker_24_center_83.mov  0.705923          0.658382     0.610645   \n",
-       "10         speaker_27_center_83.mov  0.753417          0.708372     0.654608   \n",
-       "\n",
-       "          Agreeableness Non-Neuroticism  \n",
-       "Person ID                                \n",
-       "1              0.744589        0.488671  \n",
-       "2              0.731282        0.417908  \n",
-       "3              0.685067        0.378102  \n",
-       "4               0.66223        0.348639  \n",
-       "5              0.716696         0.37802  \n",
-       "6              0.696056        0.399842  \n",
-       "7              0.788677        0.459676  \n",
-       "8              0.795205        0.447242  \n",
-       "9              0.697415        0.411988  \n",
-       "10             0.816416        0.504743  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:33:00</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
+       "                Trait    EI    SN    TF    JP\n",
+       "ID                                           \n",
+       "1            Openness  0.09 -0.03 -0.14 -0.16\n",
+       "2   Conscientiousness  0.04 -0.04  0.20  0.14\n",
+       "3        Extraversion  0.20 -0.03  0.01 -0.07\n",
+       "4       Agreeableness  0.02  0.05 -0.35  0.03\n",
+       "5     Non-Neuroticism  0.08  0.00  0.16  0.00"
       ]
      },
+     "execution_count": 6,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "\n",
+    "df_correlation_coefficients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ddd7fa82",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -1230,15 +1152,27 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
-       "      <th>Mean</th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>Match</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Metrics</th>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -1249,37 +1183,2417 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>MAE</th>\n",
-       "      <td>0.0673</td>\n",
-       "      <td>0.0789</td>\n",
-       "      <td>0.1325</td>\n",
-       "      <td>0.102</td>\n",
-       "      <td>0.1002</td>\n",
-       "      <td>0.0962</td>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>-0.185699</td>\n",
+       "      <td>0.017946</td>\n",
+       "      <td>0.083205</td>\n",
+       "      <td>0.030144</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>100.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Accuracy</th>\n",
-       "      <td>0.9327</td>\n",
-       "      <td>0.9211</td>\n",
-       "      <td>0.8675</td>\n",
-       "      <td>0.898</td>\n",
-       "      <td>0.8998</td>\n",
-       "      <td>0.9038</td>\n",
+       "      <th>3</th>\n",
+       "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.454</td>\n",
+       "      <td>-0.160520</td>\n",
+       "      <td>0.068617</td>\n",
+       "      <td>-0.278880</td>\n",
+       "      <td>0.053384</td>\n",
+       "      <td>ISFJ</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2d6btbaNdfo.000.mp4</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>0.047788</td>\n",
+       "      <td>0.002056</td>\n",
+       "      <td>-0.092138</td>\n",
+       "      <td>0.046539</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.037527</td>\n",
+       "      <td>0.002895</td>\n",
+       "      <td>-0.081646</td>\n",
+       "      <td>0.045425</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>50.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
+       "      <td>0.532</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>0.006447</td>\n",
+       "      <td>0.037143</td>\n",
+       "      <td>-0.271593</td>\n",
+       "      <td>-0.105712</td>\n",
+       "      <td>ESFP</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>-0.094752</td>\n",
+       "      <td>-0.007199</td>\n",
+       "      <td>-0.083317</td>\n",
+       "      <td>-0.132767</td>\n",
+       "      <td>INFP</td>\n",
+       "      <td>25.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>be0DQawtVkE.002.mp4</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>0.259041</td>\n",
+       "      <td>-0.027361</td>\n",
+       "      <td>-0.100093</td>\n",
+       "      <td>-0.049093</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>cLaZxEf1nE4.004.mp4</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
+       "      <td>0.558</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>0.252010</td>\n",
+       "      <td>-0.029419</td>\n",
+       "      <td>-0.087981</td>\n",
+       "      <td>-0.050501</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>0.239967</td>\n",
+       "      <td>-0.025332</td>\n",
+       "      <td>-0.090041</td>\n",
+       "      <td>-0.042964</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.248447</td>\n",
+       "      <td>-0.028874</td>\n",
+       "      <td>-0.081294</td>\n",
+       "      <td>-0.036454</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Path    OPE    CON    EXT    AGR   NNEU        EI  \\\n",
+       "Person ID                                                                     \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431 -0.185699   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454 -0.160520   \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601  0.047788   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587  0.037527   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507  0.006447   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439 -0.094752   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642  0.259041   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587  0.252010   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580  0.239967   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606  0.248447   \n",
+       "\n",
+       "                 SN        TF        JP  MBTI  Match  \n",
+       "Person ID                                             \n",
+       "2          0.017946  0.083205  0.030144  ISTJ  100.0  \n",
+       "3          0.068617 -0.278880  0.053384  ISFJ   75.0  \n",
+       "1          0.002056 -0.092138  0.046539  ESFJ   50.0  \n",
+       "4          0.002895 -0.081646  0.045425  ESFJ   50.0  \n",
+       "7          0.037143 -0.271593 -0.105712  ESFP   25.0  \n",
+       "9         -0.007199 -0.083317 -0.132767  INFP   25.0  \n",
+       "5         -0.027361 -0.100093 -0.049093  ENFP    0.0  \n",
+       "6         -0.029419 -0.087981 -0.050501  ENFP    0.0  \n",
+       "8         -0.025332 -0.090041 -0.042964  ENFP    0.0  \n",
+       "10        -0.028874 -0.081294 -0.036454  ENFP    0.0  "
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._colleague_personality_type_match(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    target_scores = [0.34, 0.56, 0.42, 0.57, 0.56],\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_MBTI_colleague_match_, name = 'MBTI_colleague_personality_type_match_en', out = True)\n",
+    "\n",
+    "# Optional\n",
+    "df = _b5.df_files_MBTI_colleague_match_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bbbb9737",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "Для определения степени выраженности персональных растройств необходимо знать коэффициенты корреляции между персональными качествами личности человека и типами личности MBTI, а также кооэффициенты корреляции между типами личности MBTI и персональными растройствами.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами личности человека и типами личности MBTI, представленных в статье [1] и кооэффициентов корреляции между типами личности MBTI и персональными растройствами [2].\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "2) Furnham A. MBTI and aberrant personality traits: dark-side trait correlates of the Myers Briggs type inventory // Psychology. - 2022. - vol. 13(5). - pp 805-815.\n",
+    "\n",
+    "Среди персональных расстройста рассматриваются следующие:\n",
+    "1) Параноидное (Paranoid) — Недоверие и подозрительность по отношению к другим; мотивы интерпретируются как злонамеренные.\n",
+    "2) Шизоидное (Schizoid) — Эмоциональная холодность и отстранённость от социальных отношений; безразличие к похвалам и критике.\n",
+    "3) Шизотипическое (Schizotypal) — Странные убеждения или магическое мышление; поведение или речь, которые кажутся странными, эксцентричными или необычными.\n",
+    "4) Антисоциальное (Antisocial) — Пренебрежение к истине; импульсивность и неспособность планировать будущее; нарушение социальных норм.\n",
+    "5) Пограничное (Borderline) — Неуместная злость; нестабильные и интенсивные отношения, которые чередуются между идеализацией и обесцениванием.\n",
+    "6) Истерическое (Histrionic) — Чрезмерная эмоциональность и стремление к вниманию; драматизация, театральное поведение и преувеличенное выражение эмоций.\n",
+    "7) Нарциссическое (Narcissistic) — Высокомерные и надменные манеры или установки, преувеличенное чувство собственной значимости и права на особое отношение.\n",
+    "8) Избегающее (Avoidant) — Социальное избегание; чувство неполноценности и повышенная чувствительность к критике или отказу.\n",
+    "9) Зависимое (Dependent) — Трудности в принятии повседневных решений без чрезмерных советов и уверений; трудности в выражении несогласия из-за страха потери поддержки или одобрения.\n",
+    "10) Обсессивно-компульсивное личностное расстройство (OCPD) — Чрезмерная озабоченность порядком, перфекционизмом, контролем и деталями; стремление к соблюдению правил, часто в ущерб гибкости и эффективности.\n",
+    "\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "2ef97e79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients_mbti = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients_mbti.index.name = 'ID'\n",
+    "df_correlation_coefficients_mbti.index += 1\n",
+    "df_correlation_coefficients_mbti.index = df_correlation_coefficients_mbti.index.map(str)\n",
+    "\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644096?token=T309xfzRosPj3v9&filename=df_disorder_correlation.csv'\n",
+    "df_correlation_coefficients_disorders = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients_disorders.index.name = 'ID'\n",
+    "df_correlation_coefficients_disorders.index += 1\n",
+    "df_correlation_coefficients_disorders.index = df_correlation_coefficients_disorders.index.map(str)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "05fe491a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>Disorder 1</th>\n",
+       "      <th>Disorder 2</th>\n",
+       "      <th>Disorder 3</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2d6btbaNdfo.000.mp4</td>\n",
+       "      <td>0.619</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.478</td>\n",
+       "      <td>0.654</td>\n",
+       "      <td>0.601</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>Narcissistic (0.034)</td>\n",
+       "      <td>Paranoid (0.033)</td>\n",
+       "      <td>Dependent (0.028)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>300gK3CnzW0.001.mp4</td>\n",
+       "      <td>0.462</td>\n",
+       "      <td>0.413</td>\n",
+       "      <td>0.416</td>\n",
+       "      <td>0.498</td>\n",
+       "      <td>0.431</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>Schizoid (0.039)</td>\n",
+       "      <td>Avoidant (0.022)</td>\n",
+       "      <td>Dependent (0.012)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>300gK3CnzW0.003.mp4</td>\n",
+       "      <td>0.468</td>\n",
+       "      <td>0.449</td>\n",
+       "      <td>0.372</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.454</td>\n",
+       "      <td>ISFJ</td>\n",
+       "      <td>Dependent (0.089)</td>\n",
+       "      <td>Narcissistic (0.087)</td>\n",
+       "      <td>Paranoid (0.082)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4vdJGgZpj4k.003.mp4</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>Narcissistic (0.03)</td>\n",
+       "      <td>Paranoid (0.029)</td>\n",
+       "      <td>Dependent (0.025)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>be0DQawtVkE.002.mp4</td>\n",
+       "      <td>0.681</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.554</td>\n",
+       "      <td>0.647</td>\n",
+       "      <td>0.642</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.067)</td>\n",
+       "      <td>Narcissistic (0.064)</td>\n",
+       "      <td>Histrionic (0.062)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>cLaZxEf1nE4.004.mp4</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.551</td>\n",
+       "      <td>0.558</td>\n",
+       "      <td>0.585</td>\n",
+       "      <td>0.587</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.063)</td>\n",
+       "      <td>Histrionic (0.06)</td>\n",
+       "      <td>Narcissistic (0.06)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>g24JGYuT74A.004.mp4</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.399</td>\n",
+       "      <td>0.410</td>\n",
+       "      <td>0.532</td>\n",
+       "      <td>0.507</td>\n",
+       "      <td>ESFP</td>\n",
+       "      <td>Narcissistic (0.09)</td>\n",
+       "      <td>Paranoid (0.085)</td>\n",
+       "      <td>Dependent (0.074)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>JZNMxa3OKHY.000.mp4</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>0.524</td>\n",
+       "      <td>0.531</td>\n",
+       "      <td>0.594</td>\n",
+       "      <td>0.580</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.061)</td>\n",
+       "      <td>Narcissistic (0.058)</td>\n",
+       "      <td>Histrionic (0.057)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>nvlqJbHk_Lc.003.mp4</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.391</td>\n",
+       "      <td>0.444</td>\n",
+       "      <td>0.439</td>\n",
+       "      <td>INFP</td>\n",
+       "      <td>Avoidant (0.036)</td>\n",
+       "      <td>Schizoid (0.035)</td>\n",
+       "      <td>Narcissistic (0.031)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>_plk5k7PBEg.003.mp4</td>\n",
+       "      <td>0.648</td>\n",
+       "      <td>0.610</td>\n",
+       "      <td>0.525</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>0.606</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.06)</td>\n",
+       "      <td>Histrionic (0.057)</td>\n",
+       "      <td>Narcissistic (0.056)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Path    OPE    CON    EXT    AGR   NNEU  MBTI  \\\n",
+       "Person ID                                                                 \n",
+       "1          2d6btbaNdfo.000.mp4  0.619  0.661  0.478  0.654  0.601  ESFJ   \n",
+       "2          300gK3CnzW0.001.mp4  0.462  0.413  0.416  0.498  0.431  ISTJ   \n",
+       "3          300gK3CnzW0.003.mp4  0.468  0.449  0.372  0.510  0.454  ISFJ   \n",
+       "4          4vdJGgZpj4k.003.mp4  0.585  0.616  0.494  0.606  0.587  ESFJ   \n",
+       "5          be0DQawtVkE.002.mp4  0.681  0.566  0.554  0.647  0.642  ENFP   \n",
+       "6          cLaZxEf1nE4.004.mp4  0.663  0.551  0.558  0.585  0.587  ENFP   \n",
+       "7          g24JGYuT74A.004.mp4  0.590  0.399  0.410  0.532  0.507  ESFP   \n",
+       "8          JZNMxa3OKHY.000.mp4  0.606  0.524  0.531  0.594  0.580  ENFP   \n",
+       "9          nvlqJbHk_Lc.003.mp4  0.511  0.465  0.391  0.444  0.439  INFP   \n",
+       "10         _plk5k7PBEg.003.mp4  0.648  0.610  0.525  0.614  0.606  ENFP   \n",
+       "\n",
+       "                     Disorder 1            Disorder 2            Disorder 3  \n",
+       "Person ID                                                                    \n",
+       "1          Narcissistic (0.034)      Paranoid (0.033)     Dependent (0.028)  \n",
+       "2              Schizoid (0.039)      Avoidant (0.022)     Dependent (0.012)  \n",
+       "3             Dependent (0.089)  Narcissistic (0.087)      Paranoid (0.082)  \n",
+       "4           Narcissistic (0.03)      Paranoid (0.029)     Dependent (0.025)  \n",
+       "5              Paranoid (0.067)  Narcissistic (0.064)    Histrionic (0.062)  \n",
+       "6              Paranoid (0.063)     Histrionic (0.06)   Narcissistic (0.06)  \n",
+       "7           Narcissistic (0.09)      Paranoid (0.085)     Dependent (0.074)  \n",
+       "8              Paranoid (0.061)  Narcissistic (0.058)    Histrionic (0.057)  \n",
+       "9              Avoidant (0.036)      Schizoid (0.035)  Narcissistic (0.031)  \n",
+       "10              Paranoid (0.06)    Histrionic (0.057)  Narcissistic (0.056)  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._colleague_personality_desorders(\n",
+    "    correlation_coefficients_mbti = df_correlation_coefficients_mbti,\n",
+    "    correlation_coefficients_disorders = df_correlation_coefficients_disorders,\n",
+    "    personality_desorder_number = 3,\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_MBTI_disorders_, name = 'MBTI_colleague_personality_type_match_fi_en', out = True)\n",
+    "\n",
+    "# Optional\n",
+    "df = _b5.df_files_MBTI_disorders_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "180a973a-c4ff-43d0-89ef-a809cd6ac00b",
+   "metadata": {},
+   "source": [
+    "### `MuPTA` (ru)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "69c7845d-be20-4632-bd83-bbbf9d47f0f0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:54:06</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:54:07</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.765745</td>\n",
+       "      <td>0.696637</td>\n",
+       "      <td>0.656309</td>\n",
+       "      <td>0.75986</td>\n",
+       "      <td>0.494141</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.686514</td>\n",
+       "      <td>0.659488</td>\n",
+       "      <td>0.611838</td>\n",
+       "      <td>0.749739</td>\n",
+       "      <td>0.420672</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.671993</td>\n",
+       "      <td>0.661216</td>\n",
+       "      <td>0.571759</td>\n",
+       "      <td>0.704542</td>\n",
+       "      <td>0.381026</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.69828</td>\n",
+       "      <td>0.59893</td>\n",
+       "      <td>0.571893</td>\n",
+       "      <td>0.674907</td>\n",
+       "      <td>0.35082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718329</td>\n",
+       "      <td>0.598986</td>\n",
+       "      <td>0.573518</td>\n",
+       "      <td>0.73201</td>\n",
+       "      <td>0.379845</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.670932</td>\n",
+       "      <td>0.671055</td>\n",
+       "      <td>0.602337</td>\n",
+       "      <td>0.708656</td>\n",
+       "      <td>0.399527</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767261</td>\n",
+       "      <td>0.658167</td>\n",
+       "      <td>0.653367</td>\n",
+       "      <td>0.801366</td>\n",
+       "      <td>0.463443</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.699837</td>\n",
+       "      <td>0.684907</td>\n",
+       "      <td>0.616671</td>\n",
+       "      <td>0.806437</td>\n",
+       "      <td>0.447853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.710566</td>\n",
+       "      <td>0.66299</td>\n",
+       "      <td>0.610562</td>\n",
+       "      <td>0.711242</td>\n",
+       "      <td>0.413696</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759404</td>\n",
+       "      <td>0.712562</td>\n",
+       "      <td>0.658357</td>\n",
+       "      <td>0.830507</td>\n",
+       "      <td>0.507612</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path  Openness Conscientiousness Extraversion  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov  0.765745          0.696637     0.656309   \n",
+       "2          speaker_06_center_83.mov  0.686514          0.659488     0.611838   \n",
+       "3          speaker_07_center_83.mov  0.671993          0.661216     0.571759   \n",
+       "4          speaker_10_center_83.mov   0.69828           0.59893     0.571893   \n",
+       "5          speaker_11_center_83.mov  0.718329          0.598986     0.573518   \n",
+       "6          speaker_15_center_83.mov  0.670932          0.671055     0.602337   \n",
+       "7          speaker_19_center_83.mov  0.767261          0.658167     0.653367   \n",
+       "8          speaker_23_center_83.mov  0.699837          0.684907     0.616671   \n",
+       "9          speaker_24_center_83.mov  0.710566           0.66299     0.610562   \n",
+       "10         speaker_27_center_83.mov  0.759404          0.712562     0.658357   \n",
+       "\n",
+       "          Agreeableness Non-Neuroticism  \n",
+       "Person ID                                \n",
+       "1               0.75986        0.494141  \n",
+       "2              0.749739        0.420672  \n",
+       "3              0.704542        0.381026  \n",
+       "4              0.674907         0.35082  \n",
+       "5               0.73201        0.379845  \n",
+       "6              0.708656        0.399527  \n",
+       "7              0.801366        0.463443  \n",
+       "8              0.806437        0.447853  \n",
+       "9              0.711242        0.413696  \n",
+       "10             0.830507        0.507612  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:54:07</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Metrics</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>MAE</th>\n",
+       "      <td>0.0706</td>\n",
+       "      <td>0.0788</td>\n",
+       "      <td>0.1328</td>\n",
+       "      <td>0.1071</td>\n",
+       "      <td>0.1002</td>\n",
+       "      <td>0.0979</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Accuracy</th>\n",
+       "      <td>0.9294</td>\n",
+       "      <td>0.9212</td>\n",
+       "      <td>0.8672</td>\n",
+       "      <td>0.8929</td>\n",
+       "      <td>0.8998</td>\n",
+       "      <td>0.9021</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
+       "Metrics                                                              \n",
+       "MAE         0.0706             0.0788        0.1328         0.1071   \n",
+       "Accuracy    0.9294             0.9212        0.8672         0.8929   \n",
+       "\n",
+       "          Non-Neuroticism    Mean  \n",
+       "Metrics                            \n",
+       "MAE                0.1002  0.0979  \n",
+       "Accuracy           0.8998  0.9021  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 21:54:07</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0979</span>, средняя точность: <span style=\"color:#1776D2\">0.9021</span> ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**--- Время выполнения: 311.791 сек. ---**</span>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import pandas as pd\n",
+    "\n",
+    "# Импорт модуля\n",
+    "from oceanai.modules.lab.build import Run\n",
+    "\n",
+    "# Создание экземпляра класса\n",
+    "_b5 = Run()\n",
+    "\n",
+    "corpus = 'mupta'\n",
+    "lang = 'ru'\n",
+    "\n",
+    "# Настройка ядра\n",
+    "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
+    "_b5.chunk_size_ = 2000000      # Размер загрузки файла из сети за 1 шаг\n",
+    "\n",
+    "# Формирование аудиомоделей\n",
+    "res_load_model_hc = _b5.load_audio_model_hc()\n",
+    "res_load_model_nn = _b5.load_audio_model_nn()\n",
+    "\n",
+    "# Загрузка весов аудиомоделей\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Формирование видеомоделей\n",
+    "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
+    "res_load_model_deep_fe = _b5.load_video_model_deep_fe()\n",
+    "res_load_model_nn = _b5.load_video_model_nn()\n",
+    "\n",
+    "# Загрузка весов видеомоделей\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
+    "res_load_text_features = _b5.load_text_features()\n",
+    "\n",
+    "# Формирование текстовых моделей \n",
+    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
+    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
+    "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
+    "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
+    "\n",
+    "# Загрузка весов текстовых моделей\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
+    "\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
+    "\n",
+    "# Формирование модели для мультимодального объединения информации\n",
+    "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
+    "\n",
+    "# Загрузка весов модели для мультимодального объединения информации\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
+    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url, force_reload = False)\n",
+    "\n",
+    "PATH_TO_DIR = './video_MuPTA/'\n",
+    "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
+    "\n",
+    "_b5.path_to_save_ = PATH_SAVE_VIDEO\n",
+    "\n",
+    "# Загрузка 10 тестовых аудиовидеозаписей из корпуса MuPTA\n",
+    "# URL: https://hci.nw.ru/en/pages/mupta-corpus\n",
+    "domain = 'https://download.sberdisk.ru/download/file/'\n",
+    "tets_name_files = [\n",
+    "    '477995979?token=2cvyk7CS0mHx2MJ&filename=speaker_06_center_83.mov',\n",
+    "    '477995980?token=jGPtBPS69uzFU6Y&filename=speaker_01_center_83.mov',\n",
+    "    '477995967?token=zCaRbNB6ht5wMPq&filename=speaker_11_center_83.mov',\n",
+    "    '477995966?token=B1rbinDYRQKrI3T&filename=speaker_15_center_83.mov',\n",
+    "    '477995978?token=dEpVDtZg1EQiEQ9&filename=speaker_07_center_83.mov',\n",
+    "    '477995961?token=o1hVjw8G45q9L9Z&filename=speaker_19_center_83.mov',\n",
+    "    '477995964?token=5K220Aqf673VHPq&filename=speaker_23_center_83.mov',\n",
+    "    '477995965?token=v1LVD2KT1cU7Lpb&filename=speaker_24_center_83.mov',\n",
+    "    '477995962?token=tmaSGyyWLA6XCy9&filename=speaker_27_center_83.mov',\n",
+    "    '477995963?token=bTpo96qNDPcwGqb&filename=speaker_10_center_83.mov',\n",
+    "]\n",
+    "\n",
+    "for curr_files in tets_name_files:\n",
+    "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
+    "\n",
+    "# Получение прогнозов\n",
+    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
+    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "\n",
+    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
+    "url_accuracy = _b5.true_traits_['mupta']['googledisk']\n",
+    "\n",
+    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "47f3fd32-1f6a-4d75-b3fb-f4deae84d996",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "Для поиска подходящего коллеги по работе необходимо знать по два коэффициента корреляции для каждого персонального качества личности человека. Эти коэффициенты должны показывать, как изменится оценка качества одного человека, если она будет больше или меньше оценки качества другого человека.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между двумя людьми в контексте отношений \"начальник-подчиненный\", представленных в статье:\n",
+    "\n",
+    "1) Kuroda S., Yamamoto I. Good boss, bad boss, workers’ mental health and productivity: Evidence from Japan // Japan & The World Economy. – 2018. – vol. 48. – pp. 106-118.\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "92f637ee-2575-49bd-ac17-fc651c906c84",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Score_comparison</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>higher</td>\n",
+       "      <td>-0.0602</td>\n",
+       "      <td>0.0471</td>\n",
+       "      <td>-0.1070</td>\n",
+       "      <td>-0.0832</td>\n",
+       "      <td>0.190</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>lower</td>\n",
+       "      <td>-0.1720</td>\n",
+       "      <td>-0.1050</td>\n",
+       "      <td>0.0772</td>\n",
+       "      <td>0.0703</td>\n",
+       "      <td>-0.229</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Score_comparison  Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
+       "ID                                                                              \n",
+       "1            higher   -0.0602             0.0471       -0.1070        -0.0832   \n",
+       "2             lower   -0.1720            -0.1050        0.0772         0.0703   \n",
+       "\n",
+       "    Non-Neuroticism  \n",
+       "ID                   \n",
+       "1             0.190  \n",
+       "2            -0.229  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/478675819?token=LuB7L1QsEY0UuSs&filename=colleague_ranking.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "df_correlation_coefficients = pd.DataFrame(\n",
+    "    df_correlation_coefficients.drop(['ID'], axis = 1)\n",
+    ")\n",
+    "\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "\n",
+    "df_correlation_coefficients"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7830c543-c445-438b-ad95-e27077ed52ca",
+   "metadata": {},
+   "source": [
+    "#### Поиск старшего коллеги"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "8d39a185-9c2a-4621-8107-a6550ea8de9a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Match</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>-0.053</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>-0.055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>-0.058</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>-0.064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>-0.211</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>-0.216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>-0.224</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>-0.224</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>-0.231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>-0.234</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
+       "Person ID                                                                    \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494 -0.053\n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508 -0.055\n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448 -0.058\n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463 -0.064\n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351 -0.211\n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381 -0.216\n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400 -0.224\n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380 -0.224\n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414 -0.231\n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421 -0.234"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Список оценок персональных качеств личности целевого человека\n",
+    "target_scores = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]\n",
+    "\n",
+    "_b5._colleague_ranking(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    target_scores = target_scores,\n",
+    "    colleague = 'major',\n",
+    "    equal_coefficients = 0.5,\n",
+    "    out = False\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'major_colleague_ranking_mupta_ru', out = True)\n",
+    "\n",
+    "# Опционно\n",
+    "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7dc09967-1654-417b-bef3-2d7aba261fe5",
+   "metadata": {},
+   "source": [
+    "#### Поиск младшего коллеги"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "a43376a5-c738-4a8a-85f6-96efe6a02ad5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Match</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>-0.007</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>-0.014</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>-0.016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>-0.019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>-0.019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>-0.025</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>-0.191</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>-0.200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>-0.212</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>-0.214</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
+       "Person ID                                                                    \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421 -0.007\n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400 -0.014\n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414 -0.016\n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380 -0.019\n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381 -0.019\n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351 -0.025\n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448 -0.191\n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463 -0.200\n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508 -0.212\n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494 -0.214"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Список оценок персональных качеств личности целевого человека\n",
+    "target_scores = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]\n",
+    "\n",
+    "_b5._colleague_ranking(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    target_scores = target_scores,\n",
+    "    colleague = 'minor',\n",
+    "    equal_coefficients = 0.5,\n",
+    "    out = False\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'minor_colleague_ranking_mupta_ru', out = True)\n",
+    "\n",
+    "# Опционно\n",
+    "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a032ddef",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "Для поиска подходящего коллеги по типу личности MBTI необходимо знать коэффициенты корреляции между личностными качествами человека и типами MBTI, а также оценки этих качеств для целевого человека.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции, представленных в статье:\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c47ab83d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.14</td>\n",
+       "      <td>-0.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>-0.04</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>-0.35</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                Trait    EI    SN    TF    JP\n",
+       "ID                                           \n",
+       "1            Openness  0.09 -0.03 -0.14 -0.16\n",
+       "2   Conscientiousness  0.04 -0.04  0.20  0.14\n",
+       "3        Extraversion  0.20 -0.03  0.01 -0.07\n",
+       "4       Agreeableness  0.02  0.05 -0.35  0.03\n",
+       "5     Non-Neuroticism  0.08  0.00  0.16  0.00"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Загрузка датафрейма с коэффициентами корреляции\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients.index.name = 'ID'\n",
+    "df_correlation_coefficients.index += 1\n",
+    "df_correlation_coefficients.index = df_correlation_coefficients.index.map(str)\n",
+    "\n",
+    "df_correlation_coefficients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "31444218",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>Match</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>0.203710</td>\n",
+       "      <td>-0.032534</td>\n",
+       "      <td>-0.306328</td>\n",
+       "      <td>-0.048136</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>0.191874</td>\n",
+       "      <td>-0.027843</td>\n",
+       "      <td>-0.287812</td>\n",
+       "      <td>-0.037850</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>0.184889</td>\n",
+       "      <td>-0.028534</td>\n",
+       "      <td>-0.263672</td>\n",
+       "      <td>-0.033835</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>0.186613</td>\n",
+       "      <td>-0.028317</td>\n",
+       "      <td>-0.264603</td>\n",
+       "      <td>-0.047660</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>0.187565</td>\n",
+       "      <td>-0.026114</td>\n",
+       "      <td>-0.292012</td>\n",
+       "      <td>-0.049261</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>0.189904</td>\n",
+       "      <td>-0.029607</td>\n",
+       "      <td>-0.265650</td>\n",
+       "      <td>-0.034305</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>0.205006</td>\n",
+       "      <td>-0.028877</td>\n",
+       "      <td>-0.323879</td>\n",
+       "      <td>-0.052313</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.194016</td>\n",
+       "      <td>-0.026570</td>\n",
+       "      <td>-0.308738</td>\n",
+       "      <td>-0.035061</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>0.193712</td>\n",
+       "      <td>-0.030591</td>\n",
+       "      <td>-0.275902</td>\n",
+       "      <td>-0.042274</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>0.285739</td>\n",
+       "      <td>-0.029510</td>\n",
+       "      <td>-0.166680</td>\n",
+       "      <td>-0.042916</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508   \n",
+       "\n",
+       "                 EI        SN        TF        JP  MBTI  Match  \n",
+       "Person ID                                                       \n",
+       "1          0.203710 -0.032534 -0.306328 -0.048136  ENFP    0.0  \n",
+       "2          0.191874 -0.027843 -0.287812 -0.037850  ENFP    0.0  \n",
+       "3          0.184889 -0.028534 -0.263672 -0.033835  ENFP    0.0  \n",
+       "4          0.186613 -0.028317 -0.264603 -0.047660  ENFP    0.0  \n",
+       "5          0.187565 -0.026114 -0.292012 -0.049261  ENFP    0.0  \n",
+       "6          0.189904 -0.029607 -0.265650 -0.034305  ENFP    0.0  \n",
+       "7          0.205006 -0.028877 -0.323879 -0.052313  ENFP    0.0  \n",
+       "8          0.194016 -0.026570 -0.308738 -0.035061  ENFP    0.0  \n",
+       "9          0.193712 -0.030591 -0.275902 -0.042274  ENFP    0.0  \n",
+       "10         0.285739 -0.029510 -0.166680 -0.042916  ENFP    0.0  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._colleague_personality_type_match(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    target_scores = [0.34, 0.56, 0.42, 0.57, 0.56],\n",
+    "    threshold = 0.5,\n",
+    "    out = False\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_MBTI_colleague_match_, name = 'MBTI_colleague_personality_type_match_ru', out = True)\n",
+    "\n",
+    "# Optional\n",
+    "df = _b5.df_files_MBTI_colleague_match_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eeddf596",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "Для определения степени выраженности персональных растройств необходимо знать коэффициенты корреляции между персональными качествами личности человека и типами личности MBTI, а также кооэффициенты корреляции между типами личности MBTI и персональными растройствами.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами личности человека и типами личности MBTI, представленных в статье [1] и кооэффициентов корреляции между типами личности MBTI и персональными растройствами [2].\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "2) Furnham A. MBTI and aberrant personality traits: dark-side trait correlates of the Myers Briggs type inventory // Psychology. - 2022. - vol. 13(5). - pp 805-815.\n",
+    "\n",
+    "Среди персональных расстройста рассматриваются следующие:\n",
+    "1) Параноидное (Paranoid) — Недоверие и подозрительность по отношению к другим; мотивы интерпретируются как злонамеренные.\n",
+    "2) Шизоидное (Schizoid) — Эмоциональная холодность и отстранённость от социальных отношений; безразличие к похвалам и критике.\n",
+    "3) Шизотипическое (Schizotypal) — Странные убеждения или магическое мышление; поведение или речь, которые кажутся странными, эксцентричными или необычными.\n",
+    "4) Антисоциальное (Antisocial) — Пренебрежение к истине; импульсивность и неспособность планировать будущее; нарушение социальных норм.\n",
+    "5) Пограничное (Borderline) — Неуместная злость; нестабильные и интенсивные отношения, которые чередуются между идеализацией и обесцениванием.\n",
+    "6) Истерическое (Histrionic) — Чрезмерная эмоциональность и стремление к вниманию; драматизация, театральное поведение и преувеличенное выражение эмоций.\n",
+    "7) Нарциссическое (Narcissistic) — Высокомерные и надменные манеры или установки, преувеличенное чувство собственной значимости и права на особое отношение.\n",
+    "8) Избегающее (Avoidant) — Социальное избегание; чувство неполноценности и повышенная чувствительность к критике или отказу.\n",
+    "9) Зависимое (Dependent) — Трудности в принятии повседневных решений без чрезмерных советов и уверений; трудности в выражении несогласия из-за страха потери поддержки или одобрения.\n",
+    "10) Обсессивно-компульсивное личностное расстройство (OCPD) — Чрезмерная озабоченность порядком, перфекционизмом, контролем и деталями; стремление к соблюдению правил, часто в ущерб гибкости и эффективности.\n",
+    "\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "5b2cb179",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients_mbti = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients_mbti.index.name = 'ID'\n",
+    "df_correlation_coefficients_mbti.index += 1\n",
+    "df_correlation_coefficients_mbti.index = df_correlation_coefficients_mbti.index.map(str)\n",
+    "\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644096?token=T309xfzRosPj3v9&filename=df_disorder_correlation.csv'\n",
+    "df_correlation_coefficients_disorders = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients_disorders.index.name = 'ID'\n",
+    "df_correlation_coefficients_disorders.index += 1\n",
+    "df_correlation_coefficients_disorders.index = df_correlation_coefficients_disorders.index.map(str)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "e4096ffc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>Disorder 1</th>\n",
+       "      <th>Disorder 2</th>\n",
+       "      <th>Disorder 3</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.766</td>\n",
+       "      <td>0.697</td>\n",
+       "      <td>0.656</td>\n",
+       "      <td>0.760</td>\n",
+       "      <td>0.494</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.121)</td>\n",
+       "      <td>Paranoid (0.119)</td>\n",
+       "      <td>Dependent (0.083)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.687</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.612</td>\n",
+       "      <td>0.750</td>\n",
+       "      <td>0.421</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.114)</td>\n",
+       "      <td>Paranoid (0.112)</td>\n",
+       "      <td>Dependent (0.078)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.672</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.705</td>\n",
+       "      <td>0.381</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.105)</td>\n",
+       "      <td>Paranoid (0.104)</td>\n",
+       "      <td>Dependent (0.071)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.698</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.572</td>\n",
+       "      <td>0.675</td>\n",
+       "      <td>0.351</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.106)</td>\n",
+       "      <td>Paranoid (0.105)</td>\n",
+       "      <td>Dependent (0.071)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.718</td>\n",
+       "      <td>0.599</td>\n",
+       "      <td>0.574</td>\n",
+       "      <td>0.732</td>\n",
+       "      <td>0.380</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.115)</td>\n",
+       "      <td>Paranoid (0.113)</td>\n",
+       "      <td>Dependent (0.079)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.671</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.709</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.107)</td>\n",
+       "      <td>Paranoid (0.105)</td>\n",
+       "      <td>Dependent (0.072)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.767</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.653</td>\n",
+       "      <td>0.801</td>\n",
+       "      <td>0.463</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.127)</td>\n",
+       "      <td>Paranoid (0.125)</td>\n",
+       "      <td>Dependent (0.087)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.700</td>\n",
+       "      <td>0.685</td>\n",
+       "      <td>0.617</td>\n",
+       "      <td>0.806</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.12)</td>\n",
+       "      <td>Paranoid (0.118)</td>\n",
+       "      <td>Dependent (0.083)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.663</td>\n",
+       "      <td>0.611</td>\n",
+       "      <td>0.711</td>\n",
+       "      <td>0.414</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Narcissistic (0.11)</td>\n",
+       "      <td>Paranoid (0.109)</td>\n",
+       "      <td>Dependent (0.074)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.759</td>\n",
+       "      <td>0.713</td>\n",
+       "      <td>0.658</td>\n",
+       "      <td>0.831</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.09)</td>\n",
+       "      <td>Narcissistic (0.088)</td>\n",
+       "      <td>Histrionic (0.073)</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path    OPE    CON    EXT    AGR   NNEU  MBTI  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov  0.766  0.697  0.656  0.760  0.494  ENFP   \n",
+       "2          speaker_06_center_83.mov  0.687  0.659  0.612  0.750  0.421  ENFP   \n",
+       "3          speaker_07_center_83.mov  0.672  0.661  0.572  0.705  0.381  ENFP   \n",
+       "4          speaker_10_center_83.mov  0.698  0.599  0.572  0.675  0.351  ENFP   \n",
+       "5          speaker_11_center_83.mov  0.718  0.599  0.574  0.732  0.380  ENFP   \n",
+       "6          speaker_15_center_83.mov  0.671  0.671  0.602  0.709  0.400  ENFP   \n",
+       "7          speaker_19_center_83.mov  0.767  0.658  0.653  0.801  0.463  ENFP   \n",
+       "8          speaker_23_center_83.mov  0.700  0.685  0.617  0.806  0.448  ENFP   \n",
+       "9          speaker_24_center_83.mov  0.711  0.663  0.611  0.711  0.414  ENFP   \n",
+       "10         speaker_27_center_83.mov  0.759  0.713  0.658  0.831  0.508  ENFP   \n",
+       "\n",
+       "                     Disorder 1            Disorder 2          Disorder 3  \n",
+       "Person ID                                                                  \n",
+       "1          Narcissistic (0.121)      Paranoid (0.119)   Dependent (0.083)  \n",
+       "2          Narcissistic (0.114)      Paranoid (0.112)   Dependent (0.078)  \n",
+       "3          Narcissistic (0.105)      Paranoid (0.104)   Dependent (0.071)  \n",
+       "4          Narcissistic (0.106)      Paranoid (0.105)   Dependent (0.071)  \n",
+       "5          Narcissistic (0.115)      Paranoid (0.113)   Dependent (0.079)  \n",
+       "6          Narcissistic (0.107)      Paranoid (0.105)   Dependent (0.072)  \n",
+       "7          Narcissistic (0.127)      Paranoid (0.125)   Dependent (0.087)  \n",
+       "8           Narcissistic (0.12)      Paranoid (0.118)   Dependent (0.083)  \n",
+       "9           Narcissistic (0.11)      Paranoid (0.109)   Dependent (0.074)  \n",
+       "10              Paranoid (0.09)  Narcissistic (0.088)  Histrionic (0.073)  "
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_b5._colleague_personality_desorders(\n",
+    "    correlation_coefficients_mbti = df_correlation_coefficients_mbti,\n",
+    "    correlation_coefficients_disorders = df_correlation_coefficients_disorders,\n",
+    "    personality_desorder_number = 3,\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
+    ")\n",
+    "\n",
+    "_b5._save_logs(df = _b5.df_files_MBTI_disorders_, name = 'MBTI_colleague_personality_type_match_fi_en', out = True)\n",
+    "\n",
+    "# Optional\n",
+    "df = _b5.df_files_MBTI_disorders_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7d55e24a-6afc-4a9c-8a2d-b459c4927225",
+   "metadata": {},
+   "source": [
+    "### `MuPTA` (en)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "6aad9dfa-d10b-46f5-b40b-18c142dbfc25",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 22:04:06</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 22:04:06</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Path</th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Person ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.59561</td>\n",
+       "      <td>0.542967</td>\n",
+       "      <td>0.440668</td>\n",
+       "      <td>0.589769</td>\n",
+       "      <td>0.515306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661347</td>\n",
+       "      <td>0.673973</td>\n",
+       "      <td>0.603208</td>\n",
+       "      <td>0.64543</td>\n",
+       "      <td>0.6431</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.439868</td>\n",
+       "      <td>0.465049</td>\n",
+       "      <td>0.284547</td>\n",
+       "      <td>0.422551</td>\n",
+       "      <td>0.396058</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.47715</td>\n",
+       "      <td>0.502563</td>\n",
+       "      <td>0.373686</td>\n",
+       "      <td>0.441372</td>\n",
+       "      <td>0.424637</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403292</td>\n",
+       "      <td>0.344359</td>\n",
+       "      <td>0.317304</td>\n",
+       "      <td>0.422228</td>\n",
+       "      <td>0.384346</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.581837</td>\n",
+       "      <td>0.562177</td>\n",
+       "      <td>0.504623</td>\n",
+       "      <td>0.602169</td>\n",
+       "      <td>0.522254</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510444</td>\n",
+       "      <td>0.448468</td>\n",
+       "      <td>0.425599</td>\n",
+       "      <td>0.451861</td>\n",
+       "      <td>0.447891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.500526</td>\n",
+       "      <td>0.541376</td>\n",
+       "      <td>0.308529</td>\n",
+       "      <td>0.441178</td>\n",
+       "      <td>0.452412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.427677</td>\n",
+       "      <td>0.511355</td>\n",
+       "      <td>0.301078</td>\n",
+       "      <td>0.434281</td>\n",
+       "      <td>0.442301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566414</td>\n",
+       "      <td>0.659169</td>\n",
+       "      <td>0.434059</td>\n",
+       "      <td>0.59122</td>\n",
+       "      <td>0.579172</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               Path  Openness Conscientiousness Extraversion  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov   0.59561          0.542967     0.440668   \n",
+       "2          speaker_06_center_83.mov  0.661347          0.673973     0.603208   \n",
+       "3          speaker_07_center_83.mov  0.439868          0.465049     0.284547   \n",
+       "4          speaker_10_center_83.mov   0.47715          0.502563     0.373686   \n",
+       "5          speaker_11_center_83.mov  0.403292          0.344359     0.317304   \n",
+       "6          speaker_15_center_83.mov  0.581837          0.562177     0.504623   \n",
+       "7          speaker_19_center_83.mov  0.510444          0.448468     0.425599   \n",
+       "8          speaker_23_center_83.mov  0.500526          0.541376     0.308529   \n",
+       "9          speaker_24_center_83.mov  0.427677          0.511355     0.301078   \n",
+       "10         speaker_27_center_83.mov  0.566414          0.659169     0.434059   \n",
+       "\n",
+       "          Agreeableness Non-Neuroticism  \n",
+       "Person ID                                \n",
+       "1              0.589769        0.515306  \n",
+       "2               0.64543          0.6431  \n",
+       "3              0.422551        0.396058  \n",
+       "4              0.441372        0.424637  \n",
+       "5              0.422228        0.384346  \n",
+       "6              0.602169        0.522254  \n",
+       "7              0.451861        0.447891  \n",
+       "8              0.441178        0.452412  \n",
+       "9              0.434281        0.442301  \n",
+       "10              0.59122        0.579172  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 22:04:06</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Openness</th>\n",
+       "      <th>Conscientiousness</th>\n",
+       "      <th>Extraversion</th>\n",
+       "      <th>Agreeableness</th>\n",
+       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Metrics</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>MAE</th>\n",
+       "      <td>0.1632</td>\n",
+       "      <td>0.1621</td>\n",
+       "      <td>0.176</td>\n",
+       "      <td>0.2589</td>\n",
+       "      <td>0.1122</td>\n",
+       "      <td>0.1745</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Accuracy</th>\n",
+       "      <td>0.8368</td>\n",
+       "      <td>0.8379</td>\n",
+       "      <td>0.824</td>\n",
+       "      <td>0.7411</td>\n",
+       "      <td>0.8878</td>\n",
+       "      <td>0.8255</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
        "Metrics                                                              \n",
-       "MAE         0.0673             0.0789        0.1325          0.102   \n",
-       "Accuracy    0.9327             0.9211        0.8675          0.898   \n",
+       "MAE         0.1632             0.1621         0.176         0.2589   \n",
+       "Accuracy    0.8368             0.8379         0.824         0.7411   \n",
        "\n",
        "          Non-Neuroticism    Mean  \n",
        "Metrics                            \n",
-       "MAE                0.1002  0.0962  \n",
-       "Accuracy           0.8998  0.9038  "
+       "MAE                0.1122  0.1745  \n",
+       "Accuracy           0.8878  0.8255  "
       ]
      },
      "metadata": {},
@@ -1288,7 +3602,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:33:00</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0962</span>, средняя точность: <span style=\"color:#1776D2\">0.9038</span> ...</span>** "
+       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2024-10-10 22:04:06</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.1745</span>, средняя точность: <span style=\"color:#1776D2\">0.8255</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1312,7 +3626,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 444.191 сек. ---**</span>"
+       "<span style=\"color:#666\">**--- Время выполнения: 302.368 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1327,7 +3641,7 @@
        "True"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1342,8 +3656,8 @@
     "# Создание экземпляра класса\n",
     "_b5 = Run()\n",
     "\n",
-    "corpus = 'mupta'\n",
-    "lang = 'ru'\n",
+    "corpus = 'fi'\n",
+    "lang = 'en'\n",
     "\n",
     "# Настройка ядра\n",
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
@@ -1354,11 +3668,11 @@
     "res_load_model_nn = _b5.load_audio_model_nn()\n",
     "\n",
     "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование видеомоделей\n",
     "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
@@ -1366,14 +3680,14 @@
     "res_load_model_nn = _b5.load_video_model_nn()\n",
     "\n",
     "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['hc']['googledisk']\n",
+    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['fe']['googledisk']\n",
+    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['video'][corpus]['nn']['googledisk']\n",
+    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
     "res_load_text_features = _b5.load_text_features()\n",
@@ -1385,17 +3699,17 @@
     "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
     "\n",
     "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['hc']['googledisk']\n",
+    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url, force_reload = False)\n",
     "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
+    "url = _b5.weights_for_big5_['text'][corpus]['nn']['googledisk']\n",
+    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url, force_reload = False)\n",
     "\n",
     "# Формирование модели для мультимодального объединения информации\n",
     "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
     "\n",
     "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
+    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['googledisk']\n",
     "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
     "\n",
     "PATH_TO_DIR = './video_MuPTA/'\n",
@@ -1427,14 +3741,14 @@
     "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
     "\n",
     "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "url_accuracy = _b5.true_traits_['mupta']['googledisk']\n",
     "\n",
     "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "47f3fd32-1f6a-4d75-b3fb-f4deae84d996",
+   "id": "023c2f19-1b4c-4a54-b003-625cd65b5f02",
    "metadata": {},
    "source": [
     "<hr>\n",
@@ -1450,8 +3764,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "92f637ee-2575-49bd-ac17-fc651c906c84",
+   "execution_count": 19,
+   "id": "0bff6386-db26-4951-aa29-7ca448b9a53c",
    "metadata": {},
    "outputs": [
     {
@@ -1527,7 +3841,7 @@
        "2            -0.229  "
       ]
      },
-     "execution_count": 7,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1549,7 +3863,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7830c543-c445-438b-ad95-e27077ed52ca",
+   "id": "a9f9d35f-e855-4e20-91b4-8dc3544f2b19",
    "metadata": {},
    "source": [
     "#### Поиск старшего коллеги"
@@ -1557,8 +3871,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "8d39a185-9c2a-4621-8107-a6550ea8de9a",
+   "execution_count": 20,
+   "id": "2c885d73-d82e-4790-9d52-2e58f3d9d022",
    "metadata": {},
    "outputs": [
     {
@@ -1603,304 +3917,104 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>-0.052</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>-0.054</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>0.091</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
-       "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>-0.057</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
-       "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>-0.063</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.080</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
        "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>-0.210</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>-0.214</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>-0.222</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
-       "      <td>0.400</td>\n",
-       "      <td>-0.223</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
-       "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>-0.229</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>-0.232</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
-       "Person ID                                                                    \n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489 -0.052\n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505 -0.054\n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447 -0.057\n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460 -0.063\n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349 -0.210\n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378 -0.214\n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378 -0.222\n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400 -0.223\n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412 -0.229\n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418 -0.232"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Список оценок персональных качеств личности целевого человека\n",
-    "target_scores = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]\n",
-    "\n",
-    "_b5._colleague_ranking(\n",
-    "    correlation_coefficients = df_correlation_coefficients,\n",
-    "    target_scores = target_scores,\n",
-    "    colleague = 'major',\n",
-    "    equal_coefficients = 0.5,\n",
-    "    out = False\n",
-    ")\n",
-    "\n",
-    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'major_colleague_ranking_mupta_ru', out = True)\n",
-    "\n",
-    "# Опционно\n",
-    "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
-    "columns_to_round = df.columns[1:]\n",
-    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7dc09967-1654-417b-bef3-2d7aba261fe5",
-   "metadata": {},
-   "source": [
-    "#### Поиск младшего коллеги"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "a43376a5-c738-4a8a-85f6-96efe6a02ad5",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Path</th>\n",
-       "      <th>OPE</th>\n",
-       "      <th>CON</th>\n",
-       "      <th>EXT</th>\n",
-       "      <th>AGR</th>\n",
-       "      <th>NNEU</th>\n",
-       "      <th>Match</th>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.073</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Person ID</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.015</td>\n",
        "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.682</td>\n",
-       "      <td>0.654</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.731</td>\n",
-       "      <td>0.418</td>\n",
-       "      <td>-0.008</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>-0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.670</td>\n",
-       "      <td>0.604</td>\n",
-       "      <td>0.696</td>\n",
-       "      <td>0.400</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
        "      <td>-0.013</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.706</td>\n",
-       "      <td>0.658</td>\n",
-       "      <td>0.611</td>\n",
-       "      <td>0.697</td>\n",
-       "      <td>0.412</td>\n",
-       "      <td>-0.016</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.713</td>\n",
-       "      <td>0.595</td>\n",
-       "      <td>0.572</td>\n",
-       "      <td>0.717</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>-0.019</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>-0.139</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.666</td>\n",
-       "      <td>0.657</td>\n",
-       "      <td>0.568</td>\n",
-       "      <td>0.685</td>\n",
-       "      <td>0.378</td>\n",
-       "      <td>-0.020</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>-0.164</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.694</td>\n",
-       "      <td>0.596</td>\n",
-       "      <td>0.571</td>\n",
-       "      <td>0.662</td>\n",
-       "      <td>0.349</td>\n",
-       "      <td>-0.025</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.683</td>\n",
-       "      <td>0.617</td>\n",
-       "      <td>0.795</td>\n",
-       "      <td>0.447</td>\n",
-       "      <td>-0.190</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.761</td>\n",
-       "      <td>0.653</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.789</td>\n",
-       "      <td>0.460</td>\n",
-       "      <td>-0.199</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.753</td>\n",
-       "      <td>0.708</td>\n",
-       "      <td>0.655</td>\n",
-       "      <td>0.816</td>\n",
-       "      <td>0.505</td>\n",
-       "      <td>-0.212</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>-0.172</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.758</td>\n",
-       "      <td>0.693</td>\n",
-       "      <td>0.650</td>\n",
-       "      <td>0.745</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>-0.213</td>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>-0.175</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1909,19 +4023,19 @@
       "text/plain": [
        "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
        "Person ID                                                                    \n",
-       "2          speaker_06_center_83.mov  0.682  0.654  0.607  0.731  0.418 -0.008\n",
-       "6          speaker_15_center_83.mov  0.664  0.670  0.604  0.696  0.400 -0.013\n",
-       "9          speaker_24_center_83.mov  0.706  0.658  0.611  0.697  0.412 -0.016\n",
-       "5          speaker_11_center_83.mov  0.713  0.595  0.572  0.717  0.378 -0.019\n",
-       "3          speaker_07_center_83.mov  0.666  0.657  0.568  0.685  0.378 -0.020\n",
-       "4          speaker_10_center_83.mov  0.694  0.596  0.571  0.662  0.349 -0.025\n",
-       "8          speaker_23_center_83.mov  0.693  0.683  0.617  0.795  0.447 -0.190\n",
-       "7          speaker_19_center_83.mov  0.761  0.653  0.651  0.789  0.460 -0.199\n",
-       "10         speaker_27_center_83.mov  0.753  0.708  0.655  0.816  0.505 -0.212\n",
-       "1          speaker_01_center_83.mov  0.758  0.693  0.650  0.745  0.489 -0.213"
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579  0.091\n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452  0.080\n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515  0.073\n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448  0.015\n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643 -0.004\n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522 -0.013\n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384 -0.139\n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396 -0.164\n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425 -0.172\n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442 -0.175"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1933,12 +4047,12 @@
     "_b5._colleague_ranking(\n",
     "    correlation_coefficients = df_correlation_coefficients,\n",
     "    target_scores = target_scores,\n",
-    "    colleague = 'minor',\n",
+    "    colleague = 'major',\n",
     "    equal_coefficients = 0.5,\n",
     "    out = False\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'minor_colleague_ranking_mupta_ru', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'major_colleague_ranking_mupta_en', out = True)\n",
     "\n",
     "# Опционно\n",
     "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
@@ -1949,42 +4063,18 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7d55e24a-6afc-4a9c-8a2d-b459c4927225",
+   "id": "51bc4b65-d97b-4f01-86bd-96492992908b",
    "metadata": {},
    "source": [
-    "### `MuPTA` (en)"
+    "#### Поиск младшего коллеги"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "6aad9dfa-d10b-46f5-b40b-18c142dbfc25",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:40:25</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Извлечение признаков (экспертных и нейросетевых) из текста ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:40:28</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#666\">&nbsp;&nbsp;&nbsp;&nbsp;10 из 10 (100.0%) ... GitHub\\OCEANAI\\docs\\source\\user_guide\\notebooks\\video_MuPTA\\test\\speaker_27_center_83.mov ...</span></p>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
+   "execution_count": 21,
+   "id": "d6b2a45c-f103-4802-bbef-1da6fce784fc",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -2007,11 +4097,12 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Path</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>OPE</th>\n",
+       "      <th>CON</th>\n",
+       "      <th>EXT</th>\n",
+       "      <th>AGR</th>\n",
+       "      <th>NNEU</th>\n",
+       "      <th>Match</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Person ID</th>\n",
@@ -2021,389 +4112,175 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.564985</td>\n",
-       "      <td>0.539052</td>\n",
-       "      <td>0.440615</td>\n",
-       "      <td>0.59251</td>\n",
-       "      <td>0.488763</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.650774</td>\n",
-       "      <td>0.663849</td>\n",
-       "      <td>0.607308</td>\n",
-       "      <td>0.643847</td>\n",
-       "      <td>0.620627</td>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>0.014</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.435976</td>\n",
-       "      <td>0.486683</td>\n",
-       "      <td>0.313828</td>\n",
-       "      <td>0.415446</td>\n",
-       "      <td>0.396618</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>0.005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.498542</td>\n",
-       "      <td>0.511243</td>\n",
-       "      <td>0.412592</td>\n",
-       "      <td>0.468947</td>\n",
-       "      <td>0.44399</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>-0.001</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.394776</td>\n",
-       "      <td>0.341608</td>\n",
-       "      <td>0.327082</td>\n",
-       "      <td>0.427304</td>\n",
-       "      <td>0.354936</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>-0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>-0.195</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566107</td>\n",
-       "      <td>0.543811</td>\n",
-       "      <td>0.492766</td>\n",
-       "      <td>0.587411</td>\n",
-       "      <td>0.499433</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>-0.198</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506271</td>\n",
-       "      <td>0.438215</td>\n",
-       "      <td>0.430894</td>\n",
-       "      <td>0.456177</td>\n",
-       "      <td>0.44075</td>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>-0.240</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486463</td>\n",
-       "      <td>0.521755</td>\n",
-       "      <td>0.309894</td>\n",
-       "      <td>0.432291</td>\n",
-       "      <td>0.433601</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>-0.260</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417404</td>\n",
-       "      <td>0.473339</td>\n",
-       "      <td>0.320714</td>\n",
-       "      <td>0.445086</td>\n",
-       "      <td>0.414649</td>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>-0.283</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526112</td>\n",
-       "      <td>0.661107</td>\n",
-       "      <td>0.443167</td>\n",
-       "      <td>0.558965</td>\n",
-       "      <td>0.554224</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                               Path  Openness Conscientiousness Extraversion  \\\n",
-       "Person ID                                                                      \n",
-       "1          speaker_01_center_83.mov  0.564985          0.539052     0.440615   \n",
-       "2          speaker_06_center_83.mov  0.650774          0.663849     0.607308   \n",
-       "3          speaker_07_center_83.mov  0.435976          0.486683     0.313828   \n",
-       "4          speaker_10_center_83.mov  0.498542          0.511243     0.412592   \n",
-       "5          speaker_11_center_83.mov  0.394776          0.341608     0.327082   \n",
-       "6          speaker_15_center_83.mov  0.566107          0.543811     0.492766   \n",
-       "7          speaker_19_center_83.mov  0.506271          0.438215     0.430894   \n",
-       "8          speaker_23_center_83.mov  0.486463          0.521755     0.309894   \n",
-       "9          speaker_24_center_83.mov  0.417404          0.473339     0.320714   \n",
-       "10         speaker_27_center_83.mov  0.526112          0.661107     0.443167   \n",
-       "\n",
-       "          Agreeableness Non-Neuroticism  \n",
-       "Person ID                                \n",
-       "1               0.59251        0.488763  \n",
-       "2              0.643847        0.620627  \n",
-       "3              0.415446        0.396618  \n",
-       "4              0.468947         0.44399  \n",
-       "5              0.427304        0.354936  \n",
-       "6              0.587411        0.499433  \n",
-       "7              0.456177         0.44075  \n",
-       "8              0.432291        0.433601  \n",
-       "9              0.445086        0.414649  \n",
-       "10             0.558965        0.554224  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:40:28</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Точность по отдельным персональным качествам личности человека ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
-       "      <th>Mean</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Metrics</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>MAE</th>\n",
-       "      <td>0.1727</td>\n",
-       "      <td>0.1672</td>\n",
-       "      <td>0.1661</td>\n",
-       "      <td>0.2579</td>\n",
-       "      <td>0.107</td>\n",
-       "      <td>0.1742</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Accuracy</th>\n",
-       "      <td>0.8273</td>\n",
-       "      <td>0.8328</td>\n",
-       "      <td>0.8339</td>\n",
-       "      <td>0.7421</td>\n",
-       "      <td>0.893</td>\n",
-       "      <td>0.8258</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>-0.304</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
-       "Metrics                                                              \n",
-       "MAE         0.1727             0.1672        0.1661         0.2579   \n",
-       "Accuracy    0.8273             0.8328        0.8339         0.7421   \n",
-       "\n",
-       "          Non-Neuroticism    Mean  \n",
-       "Metrics                            \n",
-       "MAE                 0.107  0.1742  \n",
-       "Accuracy            0.893  0.8258  "
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**[</span><span style=\"color:#1776D2\">2023-12-16 19:40:28</span><span style=\"color:#666\">]</span> <span style=\"color:#666\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.1742</span>, средняя точность: <span style=\"color:#1776D2\">0.8258</span> ...</span>** "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#008001\">**Лог файлы успешно сохранены ...**</span>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/markdown": [
-       "<span style=\"color:#666\">**--- Время выполнения: 377.119 сек. ---**</span>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "True"
+       "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
+       "Person ID                                                                    \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442  0.014\n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396  0.005\n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425 -0.001\n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384 -0.004\n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448 -0.195\n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522 -0.198\n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643 -0.240\n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452 -0.260\n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515 -0.283\n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579 -0.304"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "import os\n",
-    "import pandas as pd\n",
-    "\n",
-    "# Импорт модуля\n",
-    "from oceanai.modules.lab.build import Run\n",
-    "\n",
-    "# Создание экземпляра класса\n",
-    "_b5 = Run()\n",
-    "\n",
-    "corpus = 'fi'\n",
-    "lang = 'en'\n",
-    "\n",
-    "# Настройка ядра\n",
-    "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
-    "_b5.chunk_size_ = 2000000      # Размер загрузки файла из сети за 1 шаг\n",
-    "\n",
-    "# Формирование аудиомоделей\n",
-    "res_load_model_hc = _b5.load_audio_model_hc()\n",
-    "res_load_model_nn = _b5.load_audio_model_nn()\n",
-    "\n",
-    "# Загрузка весов аудиомоделей\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_audio_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['audio'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_audio_model_weights_nn(url = url)\n",
-    "\n",
-    "# Формирование видеомоделей\n",
-    "res_load_model_hc = _b5.load_video_model_hc(lang=lang)\n",
-    "res_load_model_deep_fe = _b5.load_video_model_deep_fe()\n",
-    "res_load_model_nn = _b5.load_video_model_nn()\n",
-    "\n",
-    "# Загрузка весов видеомоделей\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['hc']['sberdisk']\n",
-    "res_load_model_weights_hc = _b5.load_video_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['fe']['sberdisk']\n",
-    "res_load_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['video'][corpus]['nn']['sberdisk']\n",
-    "res_load_model_weights_nn = _b5.load_video_model_weights_nn(url = url)\n",
-    "\n",
-    "# Загрузка словаря с экспертными признаками (текстовая модальность)\n",
-    "res_load_text_features = _b5.load_text_features()\n",
-    "\n",
-    "# Формирование текстовых моделей \n",
-    "res_setup_translation_model = _b5.setup_translation_model() # только для русского языка\n",
-    "res_setup_translation_model = _b5.setup_bert_encoder(force_reload = False)\n",
-    "res_load_text_model_hc_fi = _b5.load_text_model_hc(corpus=corpus)\n",
-    "res_load_text_model_nn_fi = _b5.load_text_model_nn(corpus=corpus)\n",
-    "\n",
-    "# Загрузка весов текстовых моделей\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['hc']['sberdisk']\n",
-    "res_load_text_model_weights_hc_fi = _b5.load_text_model_weights_hc(url = url)\n",
-    "\n",
-    "url = _b5.weights_for_big5_['text'][corpus]['nn']['sberdisk']\n",
-    "res_load_text_model_weights_nn_fi = _b5.load_text_model_weights_nn(url = url)\n",
-    "\n",
-    "# Формирование модели для мультимодального объединения информации\n",
-    "res_load_avt_model_b5 = _b5.load_avt_model_b5()\n",
-    "\n",
-    "# Загрузка весов модели для мультимодального объединения информации\n",
-    "url = _b5.weights_for_big5_['avt'][corpus]['b5']['sberdisk']\n",
-    "res_load_avt_model_weights_b5 = _b5.load_avt_model_weights_b5(url = url)\n",
-    "\n",
-    "PATH_TO_DIR = './video_MuPTA/'\n",
-    "PATH_SAVE_VIDEO = './video_MuPTA/test/'\n",
-    "\n",
-    "_b5.path_to_save_ = PATH_SAVE_VIDEO\n",
-    "\n",
-    "# Загрузка 10 тестовых аудиовидеозаписей из корпуса MuPTA\n",
-    "# URL: https://hci.nw.ru/en/pages/mupta-corpus\n",
-    "domain = 'https://download.sberdisk.ru/download/file/'\n",
-    "tets_name_files = [\n",
-    "    '477995979?token=2cvyk7CS0mHx2MJ&filename=speaker_06_center_83.mov',\n",
-    "    '477995980?token=jGPtBPS69uzFU6Y&filename=speaker_01_center_83.mov',\n",
-    "    '477995967?token=zCaRbNB6ht5wMPq&filename=speaker_11_center_83.mov',\n",
-    "    '477995966?token=B1rbinDYRQKrI3T&filename=speaker_15_center_83.mov',\n",
-    "    '477995978?token=dEpVDtZg1EQiEQ9&filename=speaker_07_center_83.mov',\n",
-    "    '477995961?token=o1hVjw8G45q9L9Z&filename=speaker_19_center_83.mov',\n",
-    "    '477995964?token=5K220Aqf673VHPq&filename=speaker_23_center_83.mov',\n",
-    "    '477995965?token=v1LVD2KT1cU7Lpb&filename=speaker_24_center_83.mov',\n",
-    "    '477995962?token=tmaSGyyWLA6XCy9&filename=speaker_27_center_83.mov',\n",
-    "    '477995963?token=bTpo96qNDPcwGqb&filename=speaker_10_center_83.mov',\n",
-    "]\n",
-    "\n",
-    "for curr_files in tets_name_files:\n",
-    "    _b5.download_file_from_url(url = domain + curr_files, out = True)\n",
+    "# Список оценок персональных качеств личности целевого человека\n",
+    "target_scores = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]\n",
     "\n",
-    "# Получение прогнозов\n",
-    "_b5.path_to_dataset_ = PATH_TO_DIR # Директория набора данных\n",
-    "_b5.ext_ = ['.mov'] # Расширения искомых файлов\n",
+    "_b5._colleague_ranking(\n",
+    "    correlation_coefficients = df_correlation_coefficients,\n",
+    "    target_scores = target_scores,\n",
+    "    colleague = 'minor',\n",
+    "    equal_coefficients = 0.5,\n",
+    "    out = False\n",
+    ")\n",
     "\n",
-    "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['mupta']['sberdisk']\n",
+    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'minor_colleague_ranking_mupta_en', out = True)\n",
     "\n",
-    "_b5.get_avt_predictions(url_accuracy = url_accuracy, lang = lang)"
+    "# Опционно\n",
+    "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:]\n",
+    "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
+    "df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "023c2f19-1b4c-4a54-b003-625cd65b5f02",
+   "id": "a620da41",
    "metadata": {},
    "source": [
     "<hr>\n",
     "\n",
-    "Для поиска подходящего коллеги по работе необходимо знать по два коэффициента корреляции для каждого персонального качества личности человека. Эти коэффициенты должны показывать, как изменится оценка качества одного человека, если она будет больше или меньше оценки качества другого человека.\n",
+    "Для поиска подходящего коллеги по типу личности MBTI необходимо знать коэффициенты корреляции между личностными качествами человека и типами личности MBTI, а также оценки этих качеств для целевого человека.\n",
     "\n",
-    "В качестве примера предлагается использование коэффициентов корреляции между двумя людьми в контексте отношений \"начальник-подчиненный\", представленных в статье:\n",
+    "В качестве примера предлагается использование коэффициентов корреляции, представленных в статье:\n",
     "\n",
-    "1) Kuroda S., Yamamoto I. Good boss, bad boss, workers’ mental health and productivity: Evidence from Japan // Japan & The World Economy. – 2018. – vol. 48. – pp. 106-118.\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
     "\n",
     "Пользователь может установить свои коэффициенты корреляции"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "0bff6386-db26-4951-aa29-7ca448b9a53c",
+   "execution_count": 22,
+   "id": "f983123f",
    "metadata": {},
    "outputs": [
     {
@@ -2427,12 +4304,11 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>Score_comparison</th>\n",
-       "      <th>Openness</th>\n",
-       "      <th>Conscientiousness</th>\n",
-       "      <th>Extraversion</th>\n",
-       "      <th>Agreeableness</th>\n",
-       "      <th>Non-Neuroticism</th>\n",
+       "      <th>Trait</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ID</th>\n",
@@ -2441,56 +4317,72 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>higher</td>\n",
-       "      <td>-0.0602</td>\n",
-       "      <td>0.0471</td>\n",
-       "      <td>-0.1070</td>\n",
-       "      <td>-0.0832</td>\n",
-       "      <td>0.190</td>\n",
+       "      <td>Openness</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>-0.14</td>\n",
+       "      <td>-0.16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>lower</td>\n",
-       "      <td>-0.1720</td>\n",
-       "      <td>-0.1050</td>\n",
-       "      <td>0.0772</td>\n",
-       "      <td>0.0703</td>\n",
-       "      <td>-0.229</td>\n",
+       "      <td>Conscientiousness</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>-0.04</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>0.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Extraversion</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>-0.03</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>-0.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Agreeableness</td>\n",
+       "      <td>0.02</td>\n",
+       "      <td>0.05</td>\n",
+       "      <td>-0.35</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Non-Neuroticism</td>\n",
+       "      <td>0.08</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.16</td>\n",
+       "      <td>0.00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "   Score_comparison  Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
-       "ID                                                                              \n",
-       "1            higher   -0.0602             0.0471       -0.1070        -0.0832   \n",
-       "2             lower   -0.1720            -0.1050        0.0772         0.0703   \n",
-       "\n",
-       "    Non-Neuroticism  \n",
-       "ID                   \n",
-       "1             0.190  \n",
-       "2            -0.229  "
+       "                Trait    EI    SN    TF    JP\n",
+       "ID                                           \n",
+       "1            Openness  0.09 -0.03 -0.14 -0.16\n",
+       "2   Conscientiousness  0.04 -0.04  0.20  0.14\n",
+       "3        Extraversion  0.20 -0.03  0.01 -0.07\n",
+       "4       Agreeableness  0.02  0.05 -0.35  0.03\n",
+       "5     Non-Neuroticism  0.08  0.00  0.16  0.00"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Загрузка датафрейма с коэффициентами корреляции\n",
-    "url = 'https://download.sberdisk.ru/download/file/478675819?token=LuB7L1QsEY0UuSs&filename=colleague_ranking.csv'\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
     "df_correlation_coefficients = pd.read_csv(url)\n",
-    "df_correlation_coefficients = pd.DataFrame(\n",
-    "    df_correlation_coefficients.drop(['ID'], axis = 1)\n",
-    ")\n",
     "\n",
     "df_correlation_coefficients.index.name = 'ID'\n",
     "df_correlation_coefficients.index += 1\n",
@@ -2499,18 +4391,10 @@
     "df_correlation_coefficients"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "a9f9d35f-e855-4e20-91b4-8dc3544f2b19",
-   "metadata": {},
-   "source": [
-    "#### Поиск старшего коллеги"
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "2c885d73-d82e-4790-9d52-2e58f3d9d022",
+   "execution_count": 23,
+   "id": "adb4fe3b",
    "metadata": {},
    "outputs": [
     {
@@ -2540,6 +4424,11 @@
        "      <th>EXT</th>\n",
        "      <th>AGR</th>\n",
        "      <th>NNEU</th>\n",
+       "      <th>EI</th>\n",
+       "      <th>SN</th>\n",
+       "      <th>TF</th>\n",
+       "      <th>JP</th>\n",
+       "      <th>MBTI</th>\n",
        "      <th>Match</th>\n",
        "    </tr>\n",
        "    <tr>\n",
@@ -2551,166 +4440,274 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>0.069</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
-       "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>0.034</td>\n",
+       "      <th>3</th>\n",
+       "      <td>speaker_07_center_83.mov</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>-0.155235</td>\n",
+       "      <td>0.019207</td>\n",
+       "      <td>0.050250</td>\n",
+       "      <td>0.012514</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>100.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>-0.009</td>\n",
+       "      <th>5</th>\n",
+       "      <td>speaker_11_center_83.mov</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>-0.152724</td>\n",
+       "      <td>0.014281</td>\n",
+       "      <td>0.070700</td>\n",
+       "      <td>0.025861</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>100.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>-0.015</td>\n",
+       "      <th>4</th>\n",
+       "      <td>speaker_10_center_83.mov</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>-0.140376</td>\n",
+       "      <td>-0.016646</td>\n",
+       "      <td>0.250115</td>\n",
+       "      <td>0.159620</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>-0.130</td>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>-0.040020</td>\n",
+       "      <td>-0.049474</td>\n",
+       "      <td>0.117143</td>\n",
+       "      <td>0.004070</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>-0.160</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>-0.122322</td>\n",
+       "      <td>-0.020306</td>\n",
+       "      <td>0.240365</td>\n",
+       "      <td>0.148065</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>75.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>-0.163</td>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>0.040210</td>\n",
+       "      <td>0.003122</td>\n",
+       "      <td>-0.103169</td>\n",
+       "      <td>0.029258</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>50.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>-0.169</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>-0.101987</td>\n",
+       "      <td>-0.007200</td>\n",
+       "      <td>-0.078923</td>\n",
+       "      <td>-0.128220</td>\n",
+       "      <td>INFP</td>\n",
+       "      <td>25.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>-0.176</td>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>0.048690</td>\n",
+       "      <td>-0.000776</td>\n",
+       "      <td>-0.066064</td>\n",
+       "      <td>0.049778</td>\n",
+       "      <td>ENFJ</td>\n",
+       "      <td>25.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>0.271478</td>\n",
+       "      <td>-0.032624</td>\n",
+       "      <td>-0.074766</td>\n",
+       "      <td>-0.034321</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>speaker_15_center_83.mov</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
        "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
-       "      <td>0.434</td>\n",
-       "      <td>-0.183</td>\n",
+       "      <td>0.229601</td>\n",
+       "      <td>-0.024972</td>\n",
+       "      <td>-0.091174</td>\n",
+       "      <td>-0.031648</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
-       "Person ID                                                                    \n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489  0.069\n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554  0.034\n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621 -0.009\n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499 -0.015\n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355 -0.130\n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415 -0.160\n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397 -0.163\n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441 -0.169\n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444 -0.176\n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434 -0.183"
+       "                               Path    OPE    CON    EXT    AGR   NNEU  \\\n",
+       "Person ID                                                                \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442   \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522   \n",
+       "\n",
+       "                 EI        SN        TF        JP  MBTI  Match  \n",
+       "Person ID                                                       \n",
+       "3         -0.155235  0.019207  0.050250  0.012514  ISTJ  100.0  \n",
+       "5         -0.152724  0.014281  0.070700  0.025861  ISTJ  100.0  \n",
+       "4         -0.140376 -0.016646  0.250115  0.159620  INTJ   75.0  \n",
+       "8         -0.040020 -0.049474  0.117143  0.004070  INTJ   75.0  \n",
+       "9         -0.122322 -0.020306  0.240365  0.148065  INTJ   75.0  \n",
+       "1          0.040210  0.003122 -0.103169  0.029258  ESFJ   50.0  \n",
+       "7         -0.101987 -0.007200 -0.078923 -0.128220  INFP   25.0  \n",
+       "10         0.048690 -0.000776 -0.066064  0.049778  ENFJ   25.0  \n",
+       "2          0.271478 -0.032624 -0.074766 -0.034321  ENFP    0.0  \n",
+       "6          0.229601 -0.024972 -0.091174 -0.031648  ENFP    0.0  "
       ]
      },
-     "execution_count": 12,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# Список оценок персональных качеств личности целевого человека\n",
-    "target_scores = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]\n",
-    "\n",
-    "_b5._colleague_ranking(\n",
+    "_b5._colleague_personality_type_match(\n",
     "    correlation_coefficients = df_correlation_coefficients,\n",
-    "    target_scores = target_scores,\n",
-    "    colleague = 'major',\n",
-    "    equal_coefficients = 0.5,\n",
+    "    target_scores = [0.34, 0.56, 0.42, 0.57, 0.56],\n",
+    "    threshold = 0.5,\n",
     "    out = False\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'major_colleague_ranking_mupta_en', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_MBTI_colleague_match_, name = 'MBTI_colleague_personality_type_match_en', out = True)\n",
     "\n",
-    "# Опционно\n",
-    "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
-    "columns_to_round = df.columns[1:]\n",
+    "# Optional\n",
+    "df = _b5.df_files_MBTI_colleague_match_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
     "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
     "df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "51bc4b65-d97b-4f01-86bd-96492992908b",
+   "id": "b828c953",
    "metadata": {},
    "source": [
-    "#### Поиск младшего коллеги"
+    "<hr>\n",
+    "\n",
+    "Для определения степени выраженности персональных растройств необходимо знать коэффициенты корреляции между персональными качествами личности человека и типами личности MBTI, а также кооэффициенты корреляции между типами личности MBTI и персональными растройствами.\n",
+    "\n",
+    "В качестве примера предлагается использование коэффициентов корреляции между персональными качествами личности человека и типами личности MBTI, представленных в статье [1] и кооэффициентов корреляции между типами личности MBTI и персональными растройствами [2].\n",
+    "\n",
+    "1) Furnham A. The big five facets and the MBTI: The relationship between the 30 NEO-PI (R) Facets and the four Myers-Briggs Type Indicator (MBTI) scores // Psychology. - 2022. vol. 13(10). - pp. 1504-1516.\n",
+    "2) Furnham A. MBTI and aberrant personality traits: dark-side trait correlates of the Myers Briggs type inventory // Psychology. - 2022. - vol. 13(5). - pp 805-815.\n",
+    "\n",
+    "Среди персональных расстройста рассматриваются следующие:\n",
+    "1) Параноидное (Paranoid) — Недоверие и подозрительность по отношению к другим; мотивы интерпретируются как злонамеренные.\n",
+    "2) Шизоидное (Schizoid) — Эмоциональная холодность и отстранённость от социальных отношений; безразличие к похвалам и критике.\n",
+    "3) Шизотипическое (Schizotypal) — Странные убеждения или магическое мышление; поведение или речь, которые кажутся странными, эксцентричными или необычными.\n",
+    "4) Антисоциальное (Antisocial) — Пренебрежение к истине; импульсивность и неспособность планировать будущее; нарушение социальных норм.\n",
+    "5) Пограничное (Borderline) — Неуместная злость; нестабильные и интенсивные отношения, которые чередуются между идеализацией и обесцениванием.\n",
+    "6) Истерическое (Histrionic) — Чрезмерная эмоциональность и стремление к вниманию; драматизация, театральное поведение и преувеличенное выражение эмоций.\n",
+    "7) Нарциссическое (Narcissistic) — Высокомерные и надменные манеры или установки, преувеличенное чувство собственной значимости и права на особое отношение.\n",
+    "8) Избегающее (Avoidant) — Социальное избегание; чувство неполноценности и повышенная чувствительность к критике или отказу.\n",
+    "9) Зависимое (Dependent) — Трудности в принятии повседневных решений без чрезмерных советов и уверений; трудности в выражении несогласия из-за страха потери поддержки или одобрения.\n",
+    "10) Обсессивно-компульсивное личностное расстройство (OCPD) — Чрезмерная озабоченность порядком, перфекционизмом, контролем и деталями; стремление к соблюдению правил, часто в ущерб гибкости и эффективности.\n",
+    "\n",
+    "\n",
+    "Пользователь может установить свои коэффициенты корреляции"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "id": "d6b2a45c-f103-4802-bbef-1da6fce784fc",
+   "execution_count": 24,
+   "id": "8388ff45",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "url = 'https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv'\n",
+    "df_correlation_coefficients_mbti = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients_mbti.index.name = 'ID'\n",
+    "df_correlation_coefficients_mbti.index += 1\n",
+    "df_correlation_coefficients_mbti.index = df_correlation_coefficients_mbti.index.map(str)\n",
+    "\n",
+    "url = 'https://download.sberdisk.ru/download/file/493644096?token=T309xfzRosPj3v9&filename=df_disorder_correlation.csv'\n",
+    "df_correlation_coefficients_disorders = pd.read_csv(url)\n",
+    "\n",
+    "df_correlation_coefficients_disorders.index.name = 'ID'\n",
+    "df_correlation_coefficients_disorders.index += 1\n",
+    "df_correlation_coefficients_disorders.index = df_correlation_coefficients_disorders.index.map(str)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "550b8bb1",
    "metadata": {},
    "outputs": [
     {
@@ -2740,7 +4737,10 @@
        "      <th>EXT</th>\n",
        "      <th>AGR</th>\n",
        "      <th>NNEU</th>\n",
-       "      <th>Match</th>\n",
+       "      <th>MBTI</th>\n",
+       "      <th>Disorder 1</th>\n",
+       "      <th>Disorder 2</th>\n",
+       "      <th>Disorder 3</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Person ID</th>\n",
@@ -2751,150 +4751,193 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>speaker_23_center_83.mov</td>\n",
-       "      <td>0.486</td>\n",
-       "      <td>0.522</td>\n",
-       "      <td>0.310</td>\n",
-       "      <td>0.432</td>\n",
-       "      <td>0.434</td>\n",
-       "      <td>0.009</td>\n",
+       "      <th>1</th>\n",
+       "      <td>speaker_01_center_83.mov</td>\n",
+       "      <td>0.596</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.590</td>\n",
+       "      <td>0.515</td>\n",
+       "      <td>ESFJ</td>\n",
+       "      <td>Narcissistic (0.037)</td>\n",
+       "      <td>Paranoid (0.036)</td>\n",
+       "      <td>Dependent (0.03)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>speaker_24_center_83.mov</td>\n",
-       "      <td>0.417</td>\n",
-       "      <td>0.473</td>\n",
-       "      <td>0.321</td>\n",
-       "      <td>0.445</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.005</td>\n",
+       "      <th>2</th>\n",
+       "      <td>speaker_06_center_83.mov</td>\n",
+       "      <td>0.661</td>\n",
+       "      <td>0.674</td>\n",
+       "      <td>0.603</td>\n",
+       "      <td>0.645</td>\n",
+       "      <td>0.643</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.061)</td>\n",
+       "      <td>Histrionic (0.06)</td>\n",
+       "      <td>Narcissistic (0.057)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>speaker_07_center_83.mov</td>\n",
-       "      <td>0.436</td>\n",
-       "      <td>0.487</td>\n",
-       "      <td>0.314</td>\n",
-       "      <td>0.415</td>\n",
-       "      <td>0.397</td>\n",
-       "      <td>0.004</td>\n",
+       "      <td>0.440</td>\n",
+       "      <td>0.465</td>\n",
+       "      <td>0.285</td>\n",
+       "      <td>0.423</td>\n",
+       "      <td>0.396</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>Schizoid (0.033)</td>\n",
+       "      <td>Avoidant (0.019)</td>\n",
+       "      <td>Dependent (0.009)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>speaker_10_center_83.mov</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>0.511</td>\n",
-       "      <td>0.413</td>\n",
-       "      <td>0.469</td>\n",
-       "      <td>0.444</td>\n",
-       "      <td>-0.005</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>speaker_19_center_83.mov</td>\n",
-       "      <td>0.506</td>\n",
-       "      <td>0.438</td>\n",
-       "      <td>0.431</td>\n",
-       "      <td>0.456</td>\n",
+       "      <td>0.477</td>\n",
+       "      <td>0.503</td>\n",
+       "      <td>0.374</td>\n",
        "      <td>0.441</td>\n",
-       "      <td>-0.010</td>\n",
+       "      <td>0.425</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>Schizoid (0.03)</td>\n",
+       "      <td>OCPD (0.021)</td>\n",
+       "      <td>Avoidant (0.017)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>speaker_11_center_83.mov</td>\n",
-       "      <td>0.395</td>\n",
-       "      <td>0.342</td>\n",
-       "      <td>0.327</td>\n",
-       "      <td>0.427</td>\n",
-       "      <td>0.355</td>\n",
-       "      <td>-0.011</td>\n",
+       "      <td>0.403</td>\n",
+       "      <td>0.344</td>\n",
+       "      <td>0.317</td>\n",
+       "      <td>0.422</td>\n",
+       "      <td>0.384</td>\n",
+       "      <td>ISTJ</td>\n",
+       "      <td>Schizoid (0.032)</td>\n",
+       "      <td>Avoidant (0.018)</td>\n",
+       "      <td>Dependent (0.01)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>speaker_15_center_83.mov</td>\n",
-       "      <td>0.566</td>\n",
-       "      <td>0.544</td>\n",
-       "      <td>0.493</td>\n",
-       "      <td>0.587</td>\n",
-       "      <td>0.499</td>\n",
-       "      <td>-0.189</td>\n",
+       "      <td>0.582</td>\n",
+       "      <td>0.562</td>\n",
+       "      <td>0.505</td>\n",
+       "      <td>0.602</td>\n",
+       "      <td>0.522</td>\n",
+       "      <td>ENFP</td>\n",
+       "      <td>Paranoid (0.06)</td>\n",
+       "      <td>Narcissistic (0.057)</td>\n",
+       "      <td>Histrionic (0.054)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>speaker_06_center_83.mov</td>\n",
-       "      <td>0.651</td>\n",
-       "      <td>0.664</td>\n",
-       "      <td>0.607</td>\n",
-       "      <td>0.644</td>\n",
-       "      <td>0.621</td>\n",
-       "      <td>-0.232</td>\n",
+       "      <th>7</th>\n",
+       "      <td>speaker_19_center_83.mov</td>\n",
+       "      <td>0.510</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>0.426</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>0.448</td>\n",
+       "      <td>INFP</td>\n",
+       "      <td>Schizoid (0.036)</td>\n",
+       "      <td>Avoidant (0.036)</td>\n",
+       "      <td>Narcissistic (0.03)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>speaker_27_center_83.mov</td>\n",
-       "      <td>0.526</td>\n",
-       "      <td>0.661</td>\n",
-       "      <td>0.443</td>\n",
-       "      <td>0.559</td>\n",
-       "      <td>0.554</td>\n",
-       "      <td>-0.236</td>\n",
+       "      <th>8</th>\n",
+       "      <td>speaker_23_center_83.mov</td>\n",
+       "      <td>0.501</td>\n",
+       "      <td>0.541</td>\n",
+       "      <td>0.309</td>\n",
+       "      <td>0.441</td>\n",
+       "      <td>0.452</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>OCPD (0.012)</td>\n",
+       "      <td>Schizoid (0.01)</td>\n",
+       "      <td>Avoidant (0.006)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>speaker_01_center_83.mov</td>\n",
-       "      <td>0.565</td>\n",
-       "      <td>0.539</td>\n",
-       "      <td>0.441</td>\n",
-       "      <td>0.593</td>\n",
-       "      <td>0.489</td>\n",
-       "      <td>-0.271</td>\n",
+       "      <th>9</th>\n",
+       "      <td>speaker_24_center_83.mov</td>\n",
+       "      <td>0.428</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>0.301</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.442</td>\n",
+       "      <td>INTJ</td>\n",
+       "      <td>Schizoid (0.026)</td>\n",
+       "      <td>OCPD (0.02)</td>\n",
+       "      <td>Avoidant (0.015)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>speaker_27_center_83.mov</td>\n",
+       "      <td>0.566</td>\n",
+       "      <td>0.659</td>\n",
+       "      <td>0.434</td>\n",
+       "      <td>0.591</td>\n",
+       "      <td>0.579</td>\n",
+       "      <td>ENFJ</td>\n",
+       "      <td>Narcissistic (0.026)</td>\n",
+       "      <td>Paranoid (0.026)</td>\n",
+       "      <td>Dependent (0.021)</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                               Path    OPE    CON    EXT    AGR   NNEU  Match\n",
+       "                               Path    OPE    CON    EXT    AGR   NNEU  MBTI  \\\n",
+       "Person ID                                                                      \n",
+       "1          speaker_01_center_83.mov  0.596  0.543  0.441  0.590  0.515  ESFJ   \n",
+       "2          speaker_06_center_83.mov  0.661  0.674  0.603  0.645  0.643  ENFP   \n",
+       "3          speaker_07_center_83.mov  0.440  0.465  0.285  0.423  0.396  ISTJ   \n",
+       "4          speaker_10_center_83.mov  0.477  0.503  0.374  0.441  0.425  INTJ   \n",
+       "5          speaker_11_center_83.mov  0.403  0.344  0.317  0.422  0.384  ISTJ   \n",
+       "6          speaker_15_center_83.mov  0.582  0.562  0.505  0.602  0.522  ENFP   \n",
+       "7          speaker_19_center_83.mov  0.510  0.448  0.426  0.452  0.448  INFP   \n",
+       "8          speaker_23_center_83.mov  0.501  0.541  0.309  0.441  0.452  INTJ   \n",
+       "9          speaker_24_center_83.mov  0.428  0.511  0.301  0.434  0.442  INTJ   \n",
+       "10         speaker_27_center_83.mov  0.566  0.659  0.434  0.591  0.579  ENFJ   \n",
+       "\n",
+       "                     Disorder 1            Disorder 2            Disorder 3  \n",
        "Person ID                                                                    \n",
-       "8          speaker_23_center_83.mov  0.486  0.522  0.310  0.432  0.434  0.009\n",
-       "9          speaker_24_center_83.mov  0.417  0.473  0.321  0.445  0.415  0.005\n",
-       "3          speaker_07_center_83.mov  0.436  0.487  0.314  0.415  0.397  0.004\n",
-       "4          speaker_10_center_83.mov  0.499  0.511  0.413  0.469  0.444 -0.005\n",
-       "7          speaker_19_center_83.mov  0.506  0.438  0.431  0.456  0.441 -0.010\n",
-       "5          speaker_11_center_83.mov  0.395  0.342  0.327  0.427  0.355 -0.011\n",
-       "6          speaker_15_center_83.mov  0.566  0.544  0.493  0.587  0.499 -0.189\n",
-       "2          speaker_06_center_83.mov  0.651  0.664  0.607  0.644  0.621 -0.232\n",
-       "10         speaker_27_center_83.mov  0.526  0.661  0.443  0.559  0.554 -0.236\n",
-       "1          speaker_01_center_83.mov  0.565  0.539  0.441  0.593  0.489 -0.271"
+       "1          Narcissistic (0.037)      Paranoid (0.036)      Dependent (0.03)  \n",
+       "2              Paranoid (0.061)     Histrionic (0.06)  Narcissistic (0.057)  \n",
+       "3              Schizoid (0.033)      Avoidant (0.019)     Dependent (0.009)  \n",
+       "4               Schizoid (0.03)          OCPD (0.021)      Avoidant (0.017)  \n",
+       "5              Schizoid (0.032)      Avoidant (0.018)      Dependent (0.01)  \n",
+       "6               Paranoid (0.06)  Narcissistic (0.057)    Histrionic (0.054)  \n",
+       "7              Schizoid (0.036)      Avoidant (0.036)   Narcissistic (0.03)  \n",
+       "8                  OCPD (0.012)       Schizoid (0.01)      Avoidant (0.006)  \n",
+       "9              Schizoid (0.026)           OCPD (0.02)      Avoidant (0.015)  \n",
+       "10         Narcissistic (0.026)      Paranoid (0.026)     Dependent (0.021)  "
       ]
      },
-     "execution_count": 13,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# Список оценок персональных качеств личности целевого человека\n",
-    "target_scores = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]\n",
-    "\n",
-    "_b5._colleague_ranking(\n",
-    "    correlation_coefficients = df_correlation_coefficients,\n",
-    "    target_scores = target_scores,\n",
-    "    colleague = 'minor',\n",
-    "    equal_coefficients = 0.5,\n",
-    "    out = False\n",
+    "_b5._colleague_personality_desorders(\n",
+    "    correlation_coefficients_mbti = df_correlation_coefficients_mbti,\n",
+    "    correlation_coefficients_disorders = df_correlation_coefficients_disorders,\n",
+    "    personality_desorder_number = 3,\n",
+    "    threshold = 0.5,\n",
+    "    out = True\n",
     ")\n",
     "\n",
-    "_b5._save_logs(df = _b5.df_files_colleague_, name = 'minor_colleague_ranking_mupta_en', out = True)\n",
+    "_b5._save_logs(df = _b5.df_files_MBTI_disorders_, name = 'MBTI_colleague_personality_type_match_fi_en', out = True)\n",
     "\n",
-    "# Опционно\n",
-    "df = _b5.df_files_colleague_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
-    "columns_to_round = df.columns[1:]\n",
+    "# Optional\n",
+    "df = _b5.df_files_MBTI_disorders_.rename(columns = {'Openness':'OPE', 'Conscientiousness':'CON', 'Extraversion': 'EXT', 'Agreeableness': 'AGR', 'Non-Neuroticism': 'NNEU'})\n",
+    "columns_to_round = df.columns[1:6]\n",
     "df[columns_to_round] = df[columns_to_round].apply(lambda x: [round(i, 3) for i in x])\n",
     "df"
    ]
@@ -2916,7 +4959,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.11"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/user_guide/notebooks/Prediction-get_av_union_predictions.ipynb b/docs/source/user_guide/notebooks/Prediction-get_av_union_predictions.ipynb
index 491378a..ba932ee 100644
--- a/docs/source/user_guide/notebooks/Prediction-get_av_union_predictions.ipynb
+++ b/docs/source/user_guide/notebooks/Prediction-get_av_union_predictions.ipynb
@@ -64,7 +64,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:31</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">OCEANAI - персональные качества личности человека:</span>**<br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Авторы:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Карпов Алексей [<u>karpov@iias.spb.su</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Сопровождающие:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Версия: <u>1.0.0a16</u></span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Лицензия: <u>BSD License</u></span></p>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:17</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">OCEANAI - персональные качества личности человека:</span>**<br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Авторы:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Карпов Алексей [<u>karpov@iias.spb.su</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Сопровождающие:</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмина Елена [<u>ryumina_ev@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Рюмин Дмитрий [<u>dl_03.03.1991@mail.ru</u>]</span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Версия: <u>1.0.0a40</u></span><br /><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;Лицензия: <u>BSD License</u></span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -130,130 +130,118 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>TensorFlow</td>\n",
-       "      <td>2.15.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Keras</td>\n",
-       "      <td>2.15.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
        "      <td>OpenCV</td>\n",
-       "      <td>4.8.1</td>\n",
+       "      <td>4.10.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
+       "      <th>2</th>\n",
        "      <td>MediaPipe</td>\n",
-       "      <td>0.9.0</td>\n",
+       "      <td>0.10.14</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
+       "      <th>3</th>\n",
        "      <td>NumPy</td>\n",
-       "      <td>1.26.2</td>\n",
+       "      <td>1.26.4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>6</th>\n",
+       "      <th>4</th>\n",
        "      <td>SciPy</td>\n",
-       "      <td>1.11.4</td>\n",
+       "      <td>1.14.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
+       "      <th>5</th>\n",
        "      <td>Pandas</td>\n",
-       "      <td>2.1.3</td>\n",
+       "      <td>2.2.3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
+       "      <th>6</th>\n",
        "      <td>Scikit-learn</td>\n",
-       "      <td>1.3.2</td>\n",
+       "      <td>1.5.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>9</th>\n",
+       "      <th>7</th>\n",
        "      <td>OpenSmile</td>\n",
        "      <td>2.5.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
+       "      <th>8</th>\n",
        "      <td>Librosa</td>\n",
-       "      <td>0.10.1</td>\n",
+       "      <td>0.10.2.post1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
+       "      <th>9</th>\n",
        "      <td>AudioRead</td>\n",
        "      <td>3.0.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
+       "      <th>10</th>\n",
        "      <td>IPython</td>\n",
-       "      <td>8.18.1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>PyMediaInfo</td>\n",
-       "      <td>6.1.0</td>\n",
+       "      <td>8.28.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
+       "      <th>11</th>\n",
        "      <td>Requests</td>\n",
-       "      <td>2.31.0</td>\n",
+       "      <td>2.32.3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
+       "      <th>12</th>\n",
        "      <td>JupyterLab</td>\n",
-       "      <td>4.0.9</td>\n",
+       "      <td>4.2.5</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>16</th>\n",
+       "      <th>13</th>\n",
        "      <td>LIWC</td>\n",
        "      <td>0.5.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
+       "      <th>14</th>\n",
        "      <td>Transformers</td>\n",
-       "      <td>4.36.0</td>\n",
+       "      <td>4.45.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
+       "      <th>15</th>\n",
        "      <td>Sentencepiece</td>\n",
-       "      <td>0.1.99</td>\n",
+       "      <td>0.2.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>19</th>\n",
+       "      <th>16</th>\n",
        "      <td>Torch</td>\n",
-       "      <td>2.0.1+cpu</td>\n",
+       "      <td>2.4.1+cu118</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>20</th>\n",
+       "      <th>17</th>\n",
        "      <td>Torchaudio</td>\n",
-       "      <td>2.0.2+cpu</td>\n",
+       "      <td>2.4.1+cu118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Torchvision</td>\n",
+       "      <td>0.19.1+cu118</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "          Package    Version\n",
-       "1      TensorFlow     2.15.0\n",
-       "2           Keras     2.15.0\n",
-       "3          OpenCV      4.8.1\n",
-       "4       MediaPipe      0.9.0\n",
-       "5           NumPy     1.26.2\n",
-       "6           SciPy     1.11.4\n",
-       "7          Pandas      2.1.3\n",
-       "8    Scikit-learn      1.3.2\n",
-       "9       OpenSmile      2.5.0\n",
-       "10        Librosa     0.10.1\n",
-       "11      AudioRead      3.0.1\n",
-       "12        IPython     8.18.1\n",
-       "13    PyMediaInfo      6.1.0\n",
-       "14       Requests     2.31.0\n",
-       "15     JupyterLab      4.0.9\n",
-       "16           LIWC      0.5.0\n",
-       "17   Transformers     4.36.0\n",
-       "18  Sentencepiece     0.1.99\n",
-       "19          Torch  2.0.1+cpu\n",
-       "20     Torchaudio  2.0.2+cpu"
+       "          Package       Version\n",
+       "1          OpenCV        4.10.0\n",
+       "2       MediaPipe       0.10.14\n",
+       "3           NumPy        1.26.4\n",
+       "4           SciPy        1.14.1\n",
+       "5          Pandas         2.2.3\n",
+       "6    Scikit-learn         1.5.2\n",
+       "7       OpenSmile         2.5.0\n",
+       "8         Librosa  0.10.2.post1\n",
+       "9       AudioRead         3.0.1\n",
+       "10        IPython        8.28.0\n",
+       "11       Requests        2.32.3\n",
+       "12     JupyterLab         4.2.5\n",
+       "13           LIWC         0.5.0\n",
+       "14   Transformers        4.45.1\n",
+       "15  Sentencepiece         0.2.0\n",
+       "16          Torch   2.4.1+cu118\n",
+       "17     Torchaudio   2.4.1+cu118\n",
+       "18    Torchvision  0.19.1+cu118"
       ]
      },
      "metadata": {},
@@ -262,7 +250,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.006 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 0.013 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -289,7 +277,7 @@
    "source": [
     "#### Формирование нейросетевой архитектуры модели для получения оценок по экспертным признакам (аудио модальность)\n",
     "\n",
-    "> - `_b5.audio_model_hc_` - Нейросетевая модель **tf.keras.Model** для получения оценок по экспертным признакам"
+    "> - `_b5.audio_model_hc_` - Нейросетевая модель **nn.Module** для получения оценок по экспертным признакам"
    ]
   },
   {
@@ -300,7 +288,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:31</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры модели для получения оценок по экспертным признакам (аудио модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:17</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры модели для получения оценок по экспертным признакам (аудио модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -312,7 +300,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.322 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 0.013 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -337,7 +325,7 @@
    "source": [
     "#### Загрузка весов нейросетевой модели для получения оценок по экспертным признакам (аудио модальность)\n",
     "\n",
-    "> - `_b5.audio_model_hc_` - Нейросетевая модель **tf.keras.Model** для получения оценок по экспертным признакам"
+    "> - `_b5.audio_model_hc_` - Нейросетевая модель **nn.Module** для получения оценок по экспертным признакам"
    ]
   },
   {
@@ -348,7 +336,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:31</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по экспертным признакам (аудио модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:17</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по экспертным признакам (аудио модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -360,7 +348,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:32</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-05-05_11-27-55.h5</span>\" 100.0% ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:21</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-05-05_11-27-55.pth</span>\" 100.0% ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -372,7 +360,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.277 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 3.485 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -387,7 +375,7 @@
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
     "_b5.chunk_size_ = 2000000 # Размер загрузки файла из сети за 1 шаг\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio']['fi']['hc']['sberdisk']\n",
+    "url = _b5.weights_for_big5_['audio']['fi']['hc']['googledisk']\n",
     "\n",
     "res_load_audio_model_weights_hc = _b5.load_audio_model_weights_hc(\n",
     "    url = url, # Полный путь к файлу с весами нейросетевой модели\n",
@@ -404,7 +392,7 @@
    "source": [
     "#### Формирование нейросетевой архитектуры модели для получения оценок по нейросетевым признакам (аудио модальность)\n",
     "\n",
-    "> - `_b5.audio_model_nn_` - Нейросетевая модель **tf.keras.Model** для получения оценок по нейросетевым признакам"
+    "> - `_b5.audio_model_nn_` - Нейросетевая модель **nn.Module** для получения оценок по нейросетевым признакам"
    ]
   },
   {
@@ -415,7 +403,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:32</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры для получения оценок по нейросетевым признакам (аудио модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:21</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры для получения оценок по нейросетевым признакам (аудио модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -427,7 +415,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.244 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 1.067 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -452,7 +440,7 @@
    "source": [
     "#### Загрузка весов нейросетевой модели для получения оценок по нейросетевым признакам (аудио модальность)\n",
     "\n",
-    "> - `_b5.audio_model_nn_` - Нейросетевая модель **tf.keras.Model** для получения оценок по нейросетевым признакам"
+    "> - `_b5.audio_model_nn_` - Нейросетевая модель **nn.Module** для получения оценок по нейросетевым признакам"
    ]
   },
   {
@@ -463,7 +451,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:32</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по нейросетевым признакам (аудио модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:22</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по нейросетевым признакам (аудио модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -475,7 +463,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:32</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-05-03_07-46-14.h5</span>\"</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:25</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-05-03_07-46-14.pth</span>\"</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -487,7 +475,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.389 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 2.936 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -502,7 +490,7 @@
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
     "_b5.chunk_size_ = 2000000 # Размер загрузки файла из сети за 1 шаг\n",
     "\n",
-    "url = _b5.weights_for_big5_['audio']['fi']['nn']['sberdisk']\n",
+    "url = _b5.weights_for_big5_['audio']['fi']['nn']['googledisk']\n",
     "\n",
     "res_load_audio_model_weights_nn = _b5.load_audio_model_weights_nn(\n",
     "    url = url, # Полный путь к файлу с весами нейросетевой модели\n",
@@ -526,7 +514,7 @@
    "source": [
     "#### Формирование нейросетевой архитектуры модели для получения оценок по экспертным признакам (видео модальность)\n",
     "\n",
-    "> - `_b5.video_model_hc_` - Нейросетевая модель **tf.keras.Model** для получения оценок по экспертным признакам"
+    "> - `_b5.video_model_hc_` - Нейросетевая модель **nn.Module** для получения оценок по экспертным признакам"
    ]
   },
   {
@@ -537,7 +525,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:32</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры модели для получения оценок по экспертным признакам (видео модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:25</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры модели для получения оценок по экспертным признакам (видео модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -549,7 +537,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.257 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 0.002 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -575,7 +563,7 @@
    "source": [
     "#### Загрузка весов нейросетевой модели для получения оценок по экспертным признакам (видео модальность)\n",
     "\n",
-    "> - `_b5.video_model_hc_` - Нейросетевая модель **tf.keras.Model** для получения оценок по экспертным признакам"
+    "> - `_b5.video_model_hc_` - Нейросетевая модель **nn.Module** для получения оценок по экспертным признакам"
    ]
   },
   {
@@ -586,7 +574,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:32</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по экспертным признакам (видео модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:25</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по экспертным признакам (видео модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -598,7 +586,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:33</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-27_18-53-35.h5</span>\" 100.0% ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:28</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-27_18-53-35.pth</span>\" 100.0% ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -610,7 +598,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.226 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 3.298 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -625,7 +613,7 @@
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
     "_b5.chunk_size_ = 2000000 # Размер загрузки файла из сети за 1 шаг\n",
     "\n",
-    "url = _b5.weights_for_big5_['video']['fi']['hc']['sberdisk']\n",
+    "url = _b5.weights_for_big5_['video']['fi']['hc']['googledisk']\n",
     "\n",
     "res_load_video_model_weights_hc = _b5.load_video_model_weights_hc(\n",
     "    url = url, # Полный путь к файлу с весами нейросетевой модели\n",
@@ -642,7 +630,7 @@
    "source": [
     "#### Формирование нейросетевой архитектуры для получения нейросетевых признаков (видео модальность)\n",
     "\n",
-    "> - `_b5.video_model_deep_fe_` - Нейросетевая модель **tf.keras.Model** для получения нейросетевых признаков"
+    "> - `_b5.video_model_deep_fe_` - Нейросетевая модель **nn.Module** для получения нейросетевых признаков"
    ]
   },
   {
@@ -653,7 +641,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:34</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры для получения нейросетевых признаков (видео модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:28</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры для получения нейросетевых признаков (видео модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -665,7 +653,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.783 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 0.114 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -690,7 +678,7 @@
    "source": [
     "#### Загрузка весов нейросетевой модели для получения нейросетевых признаков (видео модальность)\n",
     "\n",
-    "> - `_b5.video_model_deep_fe_` - Нейросетевая модель **tf.keras.Model** для получения нейросетевых признаков"
+    "> - `_b5.video_model_deep_fe_` - Нейросетевая модель **nn.Module** для получения нейросетевых признаков"
    ]
   },
   {
@@ -701,7 +689,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:35</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения нейросетевых признаков (видео модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:28</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения нейросетевых признаков (видео модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -713,7 +701,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:40</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-11-01_12-27-07.h5</span>\" 100.0% ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-11-01_12-27-07.pth</span>\" 100.0% ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -725,7 +713,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 4.311 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 19.075 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -740,7 +728,7 @@
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
     "_b5.chunk_size_ = 2000000 # Размер загрузки файла из сети за 1 шаг\n",
     "\n",
-    "url = _b5.weights_for_big5_['video']['fi']['fe']['sberdisk']\n",
+    "url = _b5.weights_for_big5_['video']['fi']['fe']['googledisk']\n",
     "\n",
     "res_load_video_model_weights_deep_fe = _b5.load_video_model_weights_deep_fe(\n",
     "    url = url, # Полный путь к файлу с весами нейросетевой модели\n",
@@ -757,7 +745,7 @@
    "source": [
     "#### Формирование нейросетевой архитектуры модели для получения оценок по нейросетевым признакам (видео модальность)\n",
     "\n",
-    "> - `_b5.video_model_nn_` - Нейросетевая модель **tf.keras.Model** для получения оценок по нейросетевым признакам"
+    "> - `_b5.video_model_nn_` - Нейросетевая модель **nn.Module** для получения оценок по нейросетевым признакам"
    ]
   },
   {
@@ -768,7 +756,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:40</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры для получения оценок по нейросетевым признакам (видео модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:48</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевой архитектуры для получения оценок по нейросетевым признакам (видео модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -780,7 +768,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.724 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 0.023 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -805,7 +793,7 @@
    "source": [
     "#### Загрузка весов нейросетевой модели для получения оценок по нейросетевым признакам (видео модальность)\n",
     "\n",
-    "> - `_b5.video_model_nn_` - Нейросетевая модель **tf.keras.Model** для получения оценок по нейросетевым признакам"
+    "> - `_b5.video_model_nn_` - Нейросетевая модель **nn.Module** для получения оценок по нейросетевым признакам"
    ]
   },
   {
@@ -816,7 +804,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:40</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по нейросетевым признакам (видео модальность) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:48</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевой модели для получения оценок по нейросетевым признакам (видео модальность) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -828,7 +816,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:42</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-03-22_16-31-48.h5</span>\"</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:52</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-03-22_16-31-48.pth</span>\"</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -840,7 +828,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 1.355 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 4.148 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -855,7 +843,7 @@
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
     "_b5.chunk_size_ = 2000000 # Размер загрузки файла из сети за 1 шаг\n",
     "\n",
-    "url = _b5.weights_for_big5_['video']['fi']['nn']['sberdisk']\n",
+    "url = _b5.weights_for_big5_['video']['fi']['nn']['googledisk']\n",
     "\n",
     "res_load_video_model_weights_nn = _b5.load_video_model_weights_nn(\n",
     "    url = url, # Полный путь к файлу с весами нейросетевой модели\n",
@@ -879,7 +867,7 @@
    "source": [
     "#### Формирование нейросетевых архитектур моделей для получения результатов оценки персональных качеств (мультимодальное объединение)\n",
     "\n",
-    "> - `_b5.av_models_b5_` - Нейросетевые модели **tf.keras.Model** для получения результатов оценки персональных качеств"
+    "> - `_b5.av_models_b5_` - Нейросетевые модели **nn.Module** для получения результатов оценки персональных качеств"
    ]
   },
   {
@@ -890,7 +878,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:42</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевых архитектур моделей для получения результатов оценки персональных качеств (мультимодальное объединение) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:52</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Формирование нейросетевых архитектур моделей для получения результатов оценки персональных качеств (мультимодальное объединение) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -902,7 +890,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.048 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 0.002 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -927,7 +915,7 @@
    "source": [
     "#### Загрузка весов нейросетевых моделей для получения результатов оценки персональных качеств (мультимодальное объединение)\n",
     "\n",
-    "> - `_b5.av_models_b5_` - Нейросетевые модели **tf.keras.Model** для получения результатов оценки персональных качеств"
+    "> - `_b5.av_models_b5_` - Нейросетевые модели **nn.Module** для получения результатов оценки персональных качеств"
    ]
   },
   {
@@ -938,7 +926,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевых моделей для получения результатов оценки персональных качеств (мультимодальное объединение) ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:52</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка весов нейросетевых моделей для получения результатов оценки персональных качеств (мультимодальное объединение) ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -950,7 +938,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-14-35.h5</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Открытость опыту**</span>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:54</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-14-35.pth</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Открытость опыту**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -962,7 +950,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-08-10.h5</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Добросовестность**</span>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:56</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-08-10.pth</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Добросовестность**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -974,7 +962,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-17-57.h5</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Экстраверсия**</span>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:52:59</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-17-57.pth</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Экстраверсия**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -986,7 +974,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-25-11.h5</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Доброжелательность**</span>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:53:01</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-08-28_11-25-11.pth</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Доброжелательность**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -998,7 +986,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-14 22:46:47</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-06-14_21-44-09.h5</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Эмоциональная стабильность**</span>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 14:53:03</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Загрузка файла \"<span style=\"color:#1776D2\">weights_2022-06-14_21-44-09.pth</span>\" 100.0% ...</span>**  <span style=\"color:#333\">**Эмоциональная стабильность**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1010,7 +998,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 0.785 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 11.693 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1025,11 +1013,11 @@
     "_b5.path_to_save_ = './models' # Директория для сохранения файла\n",
     "_b5.chunk_size_ = 2000000 # Размер загрузки файла из сети за 1 шаг\n",
     "\n",
-    "url_openness = _b5.weights_for_big5_['av']['fi']['b5']['openness']['sberdisk']\n",
-    "url_conscientiousness = _b5.weights_for_big5_['av']['fi']['b5']['conscientiousness']['sberdisk']\n",
-    "url_extraversion = _b5.weights_for_big5_['av']['fi']['b5']['extraversion']['sberdisk']\n",
-    "url_agreeableness = _b5.weights_for_big5_['av']['fi']['b5']['agreeableness']['sberdisk']\n",
-    "url_non_neuroticism = _b5.weights_for_big5_['av']['fi']['b5']['non_neuroticism']['sberdisk']\n",
+    "url_openness = _b5.weights_for_big5_['av']['fi']['b5']['openness']['googledisk']\n",
+    "url_conscientiousness = _b5.weights_for_big5_['av']['fi']['b5']['conscientiousness']['googledisk']\n",
+    "url_extraversion = _b5.weights_for_big5_['av']['fi']['b5']['extraversion']['googledisk']\n",
+    "url_agreeableness = _b5.weights_for_big5_['av']['fi']['b5']['agreeableness']['googledisk']\n",
+    "url_non_neuroticism = _b5.weights_for_big5_['av']['fi']['b5']['non_neuroticism']['googledisk']\n",
     "\n",
     "res_load_av_models_weights_b5 = _b5.load_av_models_weights_b5(\n",
     "    url_openness = url_openness, # Открытость опыту\n",
@@ -1062,7 +1050,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-15 01:11:04</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;2000 из 2000 (100.0%) ... test80_25\\_Q4wOgixh7E.004.mp4 ...</span></p>"
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 16:17:33</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Получение прогнозов и вычисление точности (мультимодальное объединение) ...</span>**<p><span style=\"color:#333\">&nbsp;&nbsp;&nbsp;&nbsp;2000 из 2000 (100.0%) ... test80_25\\_Q4wOgixh7E.004.mp4 ...</span></p>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1100,7 +1088,7 @@
        "      <th>Non-Neuroticism</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>ID</th>\n",
+       "      <th>Person ID</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
@@ -1112,344 +1100,344 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.554249</td>\n",
-       "      <td>0.506548</td>\n",
-       "      <td>0.440194</td>\n",
-       "      <td>0.540235</td>\n",
-       "      <td>0.48605</td>\n",
+       "      <td>13kjwEtSyXc.003.mp4</td>\n",
+       "      <td>0.555285</td>\n",
+       "      <td>0.507643</td>\n",
+       "      <td>0.44126</td>\n",
+       "      <td>0.541062</td>\n",
+       "      <td>0.486505</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.558823</td>\n",
-       "      <td>0.442357</td>\n",
-       "      <td>0.50397</td>\n",
-       "      <td>0.558767</td>\n",
-       "      <td>0.521587</td>\n",
+       "      <td>1Lv72Si4GnY.000.mp4</td>\n",
+       "      <td>0.556782</td>\n",
+       "      <td>0.442179</td>\n",
+       "      <td>0.503365</td>\n",
+       "      <td>0.557368</td>\n",
+       "      <td>0.520389</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.477549</td>\n",
-       "      <td>0.568616</td>\n",
-       "      <td>0.333939</td>\n",
-       "      <td>0.491873</td>\n",
-       "      <td>0.458966</td>\n",
+       "      <td>1uC-2TZqplE.003.mp4</td>\n",
+       "      <td>0.47469</td>\n",
+       "      <td>0.568426</td>\n",
+       "      <td>0.334602</td>\n",
+       "      <td>0.493305</td>\n",
+       "      <td>0.459734</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.662656</td>\n",
-       "      <td>0.621852</td>\n",
-       "      <td>0.58996</td>\n",
-       "      <td>0.599038</td>\n",
-       "      <td>0.636035</td>\n",
+       "      <td>2Z8Xi_DTlpI.000.mp4</td>\n",
+       "      <td>0.664059</td>\n",
+       "      <td>0.623677</td>\n",
+       "      <td>0.5902</td>\n",
+       "      <td>0.599828</td>\n",
+       "      <td>0.637361</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.645876</td>\n",
-       "      <td>0.532378</td>\n",
-       "      <td>0.551939</td>\n",
-       "      <td>0.589174</td>\n",
-       "      <td>0.552269</td>\n",
+       "      <td>3df_Uk9EmwU.002.mp4</td>\n",
+       "      <td>0.639771</td>\n",
+       "      <td>0.531204</td>\n",
+       "      <td>0.54498</td>\n",
+       "      <td>0.585063</td>\n",
+       "      <td>0.545633</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.67497</td>\n",
-       "      <td>0.666972</td>\n",
-       "      <td>0.617604</td>\n",
-       "      <td>0.610567</td>\n",
-       "      <td>0.641452</td>\n",
+       "      <td>3gmc2kLV4Bo.003.mp4</td>\n",
+       "      <td>0.677814</td>\n",
+       "      <td>0.667441</td>\n",
+       "      <td>0.623028</td>\n",
+       "      <td>0.614309</td>\n",
+       "      <td>0.64445</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.39908</td>\n",
-       "      <td>0.397298</td>\n",
-       "      <td>0.335823</td>\n",
-       "      <td>0.497966</td>\n",
-       "      <td>0.39729</td>\n",
+       "      <td>3hKgh9AB3tk.003.mp4</td>\n",
+       "      <td>0.403166</td>\n",
+       "      <td>0.397586</td>\n",
+       "      <td>0.335559</td>\n",
+       "      <td>0.497902</td>\n",
+       "      <td>0.398648</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.577705</td>\n",
-       "      <td>0.597157</td>\n",
-       "      <td>0.498064</td>\n",
-       "      <td>0.640584</td>\n",
-       "      <td>0.600152</td>\n",
+       "      <td>3S72dDIm1fM.005.mp4</td>\n",
+       "      <td>0.577434</td>\n",
+       "      <td>0.597293</td>\n",
+       "      <td>0.495771</td>\n",
+       "      <td>0.639257</td>\n",
+       "      <td>0.59949</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.543675</td>\n",
-       "      <td>0.451197</td>\n",
-       "      <td>0.449555</td>\n",
-       "      <td>0.482371</td>\n",
-       "      <td>0.415256</td>\n",
+       "      <td>3tPq9fNOXZQ.000.mp4</td>\n",
+       "      <td>0.543016</td>\n",
+       "      <td>0.452105</td>\n",
+       "      <td>0.446706</td>\n",
+       "      <td>0.481398</td>\n",
+       "      <td>0.414833</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.54876</td>\n",
-       "      <td>0.51097</td>\n",
-       "      <td>0.433856</td>\n",
-       "      <td>0.579709</td>\n",
-       "      <td>0.536171</td>\n",
+       "      <td>43tayteIFRk.001.mp4</td>\n",
+       "      <td>0.547357</td>\n",
+       "      <td>0.504516</td>\n",
+       "      <td>0.428625</td>\n",
+       "      <td>0.575848</td>\n",
+       "      <td>0.526416</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.546634</td>\n",
-       "      <td>0.398485</td>\n",
-       "      <td>0.443701</td>\n",
-       "      <td>0.518107</td>\n",
-       "      <td>0.492343</td>\n",
+       "      <td>4RKQGZzPClk.000.mp4</td>\n",
+       "      <td>0.549941</td>\n",
+       "      <td>0.401322</td>\n",
+       "      <td>0.447195</td>\n",
+       "      <td>0.520176</td>\n",
+       "      <td>0.496661</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.459302</td>\n",
-       "      <td>0.427114</td>\n",
-       "      <td>0.315686</td>\n",
-       "      <td>0.495817</td>\n",
-       "      <td>0.457954</td>\n",
+       "      <td>6zm71IHOCZA.005.mp4</td>\n",
+       "      <td>0.458676</td>\n",
+       "      <td>0.430076</td>\n",
+       "      <td>0.316856</td>\n",
+       "      <td>0.497522</td>\n",
+       "      <td>0.459488</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.309097</td>\n",
-       "      <td>0.317028</td>\n",
-       "      <td>0.218514</td>\n",
-       "      <td>0.372315</td>\n",
-       "      <td>0.241697</td>\n",
+       "      <td>7qGYGbIg45c.001.mp4</td>\n",
+       "      <td>0.311843</td>\n",
+       "      <td>0.321219</td>\n",
+       "      <td>0.221201</td>\n",
+       "      <td>0.375789</td>\n",
+       "      <td>0.243581</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.643403</td>\n",
-       "      <td>0.509414</td>\n",
-       "      <td>0.483608</td>\n",
-       "      <td>0.503154</td>\n",
-       "      <td>0.550979</td>\n",
+       "      <td>8YQKwMdiaAE.003.mp4</td>\n",
+       "      <td>0.64309</td>\n",
+       "      <td>0.512177</td>\n",
+       "      <td>0.484826</td>\n",
+       "      <td>0.50723</td>\n",
+       "      <td>0.556773</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.65016</td>\n",
-       "      <td>0.840148</td>\n",
-       "      <td>0.535299</td>\n",
-       "      <td>0.710939</td>\n",
-       "      <td>0.743357</td>\n",
+       "      <td>9Crw2RtrBcY.005.mp4</td>\n",
+       "      <td>0.652284</td>\n",
+       "      <td>0.842436</td>\n",
+       "      <td>0.536853</td>\n",
+       "      <td>0.710465</td>\n",
+       "      <td>0.746347</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.598313</td>\n",
-       "      <td>0.520505</td>\n",
-       "      <td>0.450767</td>\n",
-       "      <td>0.486345</td>\n",
-       "      <td>0.561532</td>\n",
+       "      <td>9eNHxfOV2Kg.005.mp4</td>\n",
+       "      <td>0.597793</td>\n",
+       "      <td>0.528687</td>\n",
+       "      <td>0.454204</td>\n",
+       "      <td>0.491327</td>\n",
+       "      <td>0.560673</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.571537</td>\n",
-       "      <td>0.673989</td>\n",
-       "      <td>0.472203</td>\n",
-       "      <td>0.615608</td>\n",
-       "      <td>0.621064</td>\n",
+       "      <td>9J-KIPMQmqk.002.mp4</td>\n",
+       "      <td>0.573772</td>\n",
+       "      <td>0.675375</td>\n",
+       "      <td>0.47772</td>\n",
+       "      <td>0.617765</td>\n",
+       "      <td>0.626578</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.552433</td>\n",
-       "      <td>0.568787</td>\n",
-       "      <td>0.457108</td>\n",
-       "      <td>0.613188</td>\n",
-       "      <td>0.570902</td>\n",
+       "      <td>9RfE2-aTvaM.002.mp4</td>\n",
+       "      <td>0.556951</td>\n",
+       "      <td>0.572427</td>\n",
+       "      <td>0.461965</td>\n",
+       "      <td>0.616268</td>\n",
+       "      <td>0.576087</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.658695</td>\n",
-       "      <td>0.625194</td>\n",
-       "      <td>0.634877</td>\n",
-       "      <td>0.612277</td>\n",
-       "      <td>0.626052</td>\n",
+       "      <td>9_6auSk_wkY.002.mp4</td>\n",
+       "      <td>0.657349</td>\n",
+       "      <td>0.629292</td>\n",
+       "      <td>0.633481</td>\n",
+       "      <td>0.6122</td>\n",
+       "      <td>0.625547</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.660076</td>\n",
-       "      <td>0.544358</td>\n",
-       "      <td>0.64178</td>\n",
-       "      <td>0.604572</td>\n",
-       "      <td>0.628259</td>\n",
+       "      <td>aaylz9A9K80.000.mp4</td>\n",
+       "      <td>0.660384</td>\n",
+       "      <td>0.543107</td>\n",
+       "      <td>0.642626</td>\n",
+       "      <td>0.603371</td>\n",
+       "      <td>0.628241</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.543881</td>\n",
-       "      <td>0.477881</td>\n",
-       "      <td>0.407731</td>\n",
-       "      <td>0.555772</td>\n",
-       "      <td>0.499664</td>\n",
+       "      <td>Af_F0IzHK6o.002.mp4</td>\n",
+       "      <td>0.544945</td>\n",
+       "      <td>0.477108</td>\n",
+       "      <td>0.40823</td>\n",
+       "      <td>0.557337</td>\n",
+       "      <td>0.500925</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.537325</td>\n",
-       "      <td>0.46375</td>\n",
-       "      <td>0.419255</td>\n",
-       "      <td>0.499785</td>\n",
-       "      <td>0.455146</td>\n",
+       "      <td>Ah5PEPT4xbo.000.mp4</td>\n",
+       "      <td>0.543</td>\n",
+       "      <td>0.466857</td>\n",
+       "      <td>0.422051</td>\n",
+       "      <td>0.502522</td>\n",
+       "      <td>0.461761</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.464761</td>\n",
-       "      <td>0.434816</td>\n",
-       "      <td>0.346836</td>\n",
-       "      <td>0.428429</td>\n",
-       "      <td>0.358087</td>\n",
+       "      <td>AotbiNsU85A.003.mp4</td>\n",
+       "      <td>0.462694</td>\n",
+       "      <td>0.434322</td>\n",
+       "      <td>0.346588</td>\n",
+       "      <td>0.428535</td>\n",
+       "      <td>0.356066</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.633951</td>\n",
-       "      <td>0.63333</td>\n",
-       "      <td>0.584644</td>\n",
-       "      <td>0.615227</td>\n",
-       "      <td>0.608006</td>\n",
+       "      <td>BLc_GvsbI1U.001.mp4</td>\n",
+       "      <td>0.634953</td>\n",
+       "      <td>0.633947</td>\n",
+       "      <td>0.585365</td>\n",
+       "      <td>0.616067</td>\n",
+       "      <td>0.608561</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.4517</td>\n",
-       "      <td>0.574346</td>\n",
-       "      <td>0.350136</td>\n",
-       "      <td>0.526873</td>\n",
-       "      <td>0.468283</td>\n",
+       "      <td>bLOSPQ8MAC8.005.mp4</td>\n",
+       "      <td>0.453969</td>\n",
+       "      <td>0.581637</td>\n",
+       "      <td>0.349498</td>\n",
+       "      <td>0.528774</td>\n",
+       "      <td>0.470935</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.602848</td>\n",
-       "      <td>0.592382</td>\n",
-       "      <td>0.494679</td>\n",
-       "      <td>0.539232</td>\n",
-       "      <td>0.505865</td>\n",
+       "      <td>bPLhV0PGR50.001.mp4</td>\n",
+       "      <td>0.601943</td>\n",
+       "      <td>0.593242</td>\n",
+       "      <td>0.493392</td>\n",
+       "      <td>0.540426</td>\n",
+       "      <td>0.504249</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.586638</td>\n",
-       "      <td>0.521421</td>\n",
-       "      <td>0.485391</td>\n",
-       "      <td>0.530296</td>\n",
-       "      <td>0.535499</td>\n",
+       "      <td>bYXRyimxh7A.001.mp4</td>\n",
+       "      <td>0.58827</td>\n",
+       "      <td>0.525422</td>\n",
+       "      <td>0.485068</td>\n",
+       "      <td>0.532413</td>\n",
+       "      <td>0.535188</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.689552</td>\n",
-       "      <td>0.643902</td>\n",
-       "      <td>0.695799</td>\n",
-       "      <td>0.646209</td>\n",
-       "      <td>0.686243</td>\n",
+       "      <td>ch2BcBv4SdQ.003.mp4</td>\n",
+       "      <td>0.690328</td>\n",
+       "      <td>0.647787</td>\n",
+       "      <td>0.699549</td>\n",
+       "      <td>0.64751</td>\n",
+       "      <td>0.689377</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.583505</td>\n",
-       "      <td>0.564313</td>\n",
-       "      <td>0.502263</td>\n",
-       "      <td>0.554502</td>\n",
-       "      <td>0.539899</td>\n",
+       "      <td>cpch8WDydcM.004.mp4</td>\n",
+       "      <td>0.585724</td>\n",
+       "      <td>0.567717</td>\n",
+       "      <td>0.503909</td>\n",
+       "      <td>0.556293</td>\n",
+       "      <td>0.542365</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>30</th>\n",
-       "      <td>E:\\Databases\\FirstImpressionsV2\\test\\test80_01...</td>\n",
-       "      <td>0.642695</td>\n",
-       "      <td>0.588222</td>\n",
-       "      <td>0.617706</td>\n",
-       "      <td>0.615312</td>\n",
-       "      <td>0.626649</td>\n",
+       "      <td>De4i7-FX9Og.002.mp4</td>\n",
+       "      <td>0.64488</td>\n",
+       "      <td>0.587383</td>\n",
+       "      <td>0.618146</td>\n",
+       "      <td>0.614909</td>\n",
+       "      <td>0.62523</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                                                 Path  Openness  \\\n",
-       "ID                                                                \n",
-       "1   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.554249   \n",
-       "2   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.558823   \n",
-       "3   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.477549   \n",
-       "4   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.662656   \n",
-       "5   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.645876   \n",
-       "6   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...   0.67497   \n",
-       "7   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...   0.39908   \n",
-       "8   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.577705   \n",
-       "9   E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.543675   \n",
-       "10  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...   0.54876   \n",
-       "11  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.546634   \n",
-       "12  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.459302   \n",
-       "13  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.309097   \n",
-       "14  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.643403   \n",
-       "15  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...   0.65016   \n",
-       "16  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.598313   \n",
-       "17  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.571537   \n",
-       "18  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.552433   \n",
-       "19  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.658695   \n",
-       "20  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.660076   \n",
-       "21  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.543881   \n",
-       "22  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.537325   \n",
-       "23  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.464761   \n",
-       "24  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.633951   \n",
-       "25  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...    0.4517   \n",
-       "26  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.602848   \n",
-       "27  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.586638   \n",
-       "28  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.689552   \n",
-       "29  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.583505   \n",
-       "30  E:\\Databases\\FirstImpressionsV2\\test\\test80_01...  0.642695   \n",
+       "                          Path  Openness Conscientiousness Extraversion  \\\n",
+       "Person ID                                                                 \n",
+       "1          13kjwEtSyXc.003.mp4  0.555285          0.507643      0.44126   \n",
+       "2          1Lv72Si4GnY.000.mp4  0.556782          0.442179     0.503365   \n",
+       "3          1uC-2TZqplE.003.mp4   0.47469          0.568426     0.334602   \n",
+       "4          2Z8Xi_DTlpI.000.mp4  0.664059          0.623677       0.5902   \n",
+       "5          3df_Uk9EmwU.002.mp4  0.639771          0.531204      0.54498   \n",
+       "6          3gmc2kLV4Bo.003.mp4  0.677814          0.667441     0.623028   \n",
+       "7          3hKgh9AB3tk.003.mp4  0.403166          0.397586     0.335559   \n",
+       "8          3S72dDIm1fM.005.mp4  0.577434          0.597293     0.495771   \n",
+       "9          3tPq9fNOXZQ.000.mp4  0.543016          0.452105     0.446706   \n",
+       "10         43tayteIFRk.001.mp4  0.547357          0.504516     0.428625   \n",
+       "11         4RKQGZzPClk.000.mp4  0.549941          0.401322     0.447195   \n",
+       "12         6zm71IHOCZA.005.mp4  0.458676          0.430076     0.316856   \n",
+       "13         7qGYGbIg45c.001.mp4  0.311843          0.321219     0.221201   \n",
+       "14         8YQKwMdiaAE.003.mp4   0.64309          0.512177     0.484826   \n",
+       "15         9Crw2RtrBcY.005.mp4  0.652284          0.842436     0.536853   \n",
+       "16         9eNHxfOV2Kg.005.mp4  0.597793          0.528687     0.454204   \n",
+       "17         9J-KIPMQmqk.002.mp4  0.573772          0.675375      0.47772   \n",
+       "18         9RfE2-aTvaM.002.mp4  0.556951          0.572427     0.461965   \n",
+       "19         9_6auSk_wkY.002.mp4  0.657349          0.629292     0.633481   \n",
+       "20         aaylz9A9K80.000.mp4  0.660384          0.543107     0.642626   \n",
+       "21         Af_F0IzHK6o.002.mp4  0.544945          0.477108      0.40823   \n",
+       "22         Ah5PEPT4xbo.000.mp4     0.543          0.466857     0.422051   \n",
+       "23         AotbiNsU85A.003.mp4  0.462694          0.434322     0.346588   \n",
+       "24         BLc_GvsbI1U.001.mp4  0.634953          0.633947     0.585365   \n",
+       "25         bLOSPQ8MAC8.005.mp4  0.453969          0.581637     0.349498   \n",
+       "26         bPLhV0PGR50.001.mp4  0.601943          0.593242     0.493392   \n",
+       "27         bYXRyimxh7A.001.mp4   0.58827          0.525422     0.485068   \n",
+       "28         ch2BcBv4SdQ.003.mp4  0.690328          0.647787     0.699549   \n",
+       "29         cpch8WDydcM.004.mp4  0.585724          0.567717     0.503909   \n",
+       "30         De4i7-FX9Og.002.mp4   0.64488          0.587383     0.618146   \n",
        "\n",
-       "   Conscientiousness Extraversion Agreeableness Non-Neuroticism  \n",
-       "ID                                                               \n",
-       "1           0.506548     0.440194      0.540235         0.48605  \n",
-       "2           0.442357      0.50397      0.558767        0.521587  \n",
-       "3           0.568616     0.333939      0.491873        0.458966  \n",
-       "4           0.621852      0.58996      0.599038        0.636035  \n",
-       "5           0.532378     0.551939      0.589174        0.552269  \n",
-       "6           0.666972     0.617604      0.610567        0.641452  \n",
-       "7           0.397298     0.335823      0.497966         0.39729  \n",
-       "8           0.597157     0.498064      0.640584        0.600152  \n",
-       "9           0.451197     0.449555      0.482371        0.415256  \n",
-       "10           0.51097     0.433856      0.579709        0.536171  \n",
-       "11          0.398485     0.443701      0.518107        0.492343  \n",
-       "12          0.427114     0.315686      0.495817        0.457954  \n",
-       "13          0.317028     0.218514      0.372315        0.241697  \n",
-       "14          0.509414     0.483608      0.503154        0.550979  \n",
-       "15          0.840148     0.535299      0.710939        0.743357  \n",
-       "16          0.520505     0.450767      0.486345        0.561532  \n",
-       "17          0.673989     0.472203      0.615608        0.621064  \n",
-       "18          0.568787     0.457108      0.613188        0.570902  \n",
-       "19          0.625194     0.634877      0.612277        0.626052  \n",
-       "20          0.544358      0.64178      0.604572        0.628259  \n",
-       "21          0.477881     0.407731      0.555772        0.499664  \n",
-       "22           0.46375     0.419255      0.499785        0.455146  \n",
-       "23          0.434816     0.346836      0.428429        0.358087  \n",
-       "24           0.63333     0.584644      0.615227        0.608006  \n",
-       "25          0.574346     0.350136      0.526873        0.468283  \n",
-       "26          0.592382     0.494679      0.539232        0.505865  \n",
-       "27          0.521421     0.485391      0.530296        0.535499  \n",
-       "28          0.643902     0.695799      0.646209        0.686243  \n",
-       "29          0.564313     0.502263      0.554502        0.539899  \n",
-       "30          0.588222     0.617706      0.615312        0.626649  "
+       "          Agreeableness Non-Neuroticism  \n",
+       "Person ID                                \n",
+       "1              0.541062        0.486505  \n",
+       "2              0.557368        0.520389  \n",
+       "3              0.493305        0.459734  \n",
+       "4              0.599828        0.637361  \n",
+       "5              0.585063        0.545633  \n",
+       "6              0.614309         0.64445  \n",
+       "7              0.497902        0.398648  \n",
+       "8              0.639257         0.59949  \n",
+       "9              0.481398        0.414833  \n",
+       "10             0.575848        0.526416  \n",
+       "11             0.520176        0.496661  \n",
+       "12             0.497522        0.459488  \n",
+       "13             0.375789        0.243581  \n",
+       "14              0.50723        0.556773  \n",
+       "15             0.710465        0.746347  \n",
+       "16             0.491327        0.560673  \n",
+       "17             0.617765        0.626578  \n",
+       "18             0.616268        0.576087  \n",
+       "19               0.6122        0.625547  \n",
+       "20             0.603371        0.628241  \n",
+       "21             0.557337        0.500925  \n",
+       "22             0.502522        0.461761  \n",
+       "23             0.428535        0.356066  \n",
+       "24             0.616067        0.608561  \n",
+       "25             0.528774        0.470935  \n",
+       "26             0.540426        0.504249  \n",
+       "27             0.532413        0.535188  \n",
+       "28              0.64751        0.689377  \n",
+       "29             0.556293        0.542365  \n",
+       "30             0.614909         0.62523  "
       ]
      },
      "metadata": {},
@@ -1458,7 +1446,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-15 01:11:04</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Точность по отдельным персональным качествам личности человека ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 16:17:33</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Точность по отдельным персональным качествам личности человека ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1508,20 +1496,20 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MAE</th>\n",
-       "      <td>0.0845</td>\n",
+       "      <td>0.0844</td>\n",
        "      <td>0.0802</td>\n",
        "      <td>0.0793</td>\n",
        "      <td>0.0858</td>\n",
-       "      <td>0.0847</td>\n",
+       "      <td>0.0848</td>\n",
        "      <td>0.0829</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.9155</td>\n",
+       "      <td>0.9156</td>\n",
        "      <td>0.9198</td>\n",
        "      <td>0.9207</td>\n",
        "      <td>0.9142</td>\n",
-       "      <td>0.9153</td>\n",
+       "      <td>0.9152</td>\n",
        "      <td>0.9171</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -1531,13 +1519,13 @@
       "text/plain": [
        "          Openness  Conscientiousness  Extraversion  Agreeableness  \\\n",
        "Metrics                                                              \n",
-       "MAE         0.0845             0.0802        0.0793         0.0858   \n",
-       "Accuracy    0.9155             0.9198        0.9207         0.9142   \n",
+       "MAE         0.0844             0.0802        0.0793         0.0858   \n",
+       "Accuracy    0.9156             0.9198        0.9207         0.9142   \n",
        "\n",
        "          Non-Neuroticism    Mean  \n",
        "Metrics                            \n",
-       "MAE                0.0847  0.0829  \n",
-       "Accuracy           0.9153  0.9171  "
+       "MAE                0.0848  0.0829  \n",
+       "Accuracy           0.9152  0.9171  "
       ]
      },
      "metadata": {},
@@ -1546,7 +1534,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2023-12-15 01:11:04</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0829</span>, средняя точность: <span style=\"color:#1776D2\">0.9171</span> ...</span>** "
+       "<span style=\"color:#333\">**[</span><span style=\"color:#1776D2\">2024-10-09 16:17:33</span><span style=\"color:#333\">]</span> <span style=\"color:#333\">Средняя средних абсолютных ошибок: <span style=\"color:#1776D2\">0.0829</span>, средняя точность: <span style=\"color:#1776D2\">0.9171</span> ...</span>** "
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1570,7 +1558,7 @@
     {
      "data": {
       "text/markdown": [
-       "<span style=\"color:#333\">**--- Время выполнения: 8654.754 сек. ---**</span>"
+       "<span style=\"color:#333\">**--- Время выполнения: 5069.328 сек. ---**</span>"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1600,7 +1588,7 @@
     "_b5.ext_ = ['.mp4'] # Расширения искомых файлов\n",
     "\n",
     "# Полный путь к файлу с верными предсказаниями для подсчета точности\n",
-    "url_accuracy = _b5.true_traits_['fi']['sberdisk']\n",
+    "url_accuracy = _b5.true_traits_['fi']['googledisk']\n",
     "\n",
     "_b5.get_av_union_predictions(\n",
     "    depth = 1,         # Глубина иерархии для получения аудио и видеоданных\n",
@@ -1638,7 +1626,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.11"
   }
  },
  "nbformat": 4,
diff --git a/oceanai/modules/core/core.py b/oceanai/modules/core/core.py
index d3e8d06..ac9c7f3 100644
--- a/oceanai/modules/core/core.py
+++ b/oceanai/modules/core/core.py
@@ -4161,7 +4161,6 @@ def _professional_match(
             df_files (pd.DataFrame): **DataFrame** c данными
             correlation_coefficients (pd.DataFrame): **DataFrame** c коэффициентами корреляции
             personality_type (str): Персональный тип по версии MBTI
-            col_name_ocean (str): Столбец с названиями персональных качеств личности человека
             threshold (float): Порог для оценок полярности качеств (например, интроверт < 0.55, экстраверт > 0.55)
             out (bool): Отображение
 
@@ -4204,7 +4203,10 @@ def _professional_match(
 
                     name_mbti = correlation_coefficients.columns[1:]
 
-                    need_type = self.dict_mbti[personality_type]
+                    if len(personality_type) != 4:
+                        need_type = self.dict_mbti[personality_type]
+                    else:
+                        need_type = personality_type
 
                     for path in range(len(self._df_files)):
                         curr_traits = self._df_files.iloc[path].values[1:]
@@ -4233,9 +4235,9 @@ def _professional_match(
                         by=["MBTI_Score"], ascending=False
                     )
 
-                    self._df_files_MBTI_job_match.index.name = self._keys_id
-                    self._df_files_MBTI_job_match.index += 1
-                    self._df_files_MBTI_job_match.index = self._df_files_MBTI_job_match.index.map(str)
+                    # self._df_files_MBTI_job_match.index.name = self._keys_id
+                    # self._df_files_MBTI_job_match.index += 1
+                    # self._df_files_MBTI_job_match.index = self._df_files_MBTI_job_match.index.map(str)
 
                 except Exception:
                     self._other_error(self._unknown_err, out=out)
@@ -4261,7 +4263,6 @@ def _colleague_personality_type_match(
             df_files (pd.DataFrame): **DataFrame** c данными
             correlation_coefficients (pd.DataFrame): **DataFrame** c коэффициентами корреляции
             target_scores (List[float]): Список оценок персональных качеств личности целевого человека
-            col_name_ocean (str): Столбец с названиями персональных качеств личности человека
             threshold (float): Порог для оценок полярности качеств (например, интроверт < 0.55, экстраверт > 0.55)
             out (bool): Отображение
 
@@ -4340,7 +4341,7 @@ def _colleague_personality_type_match(
                             ]
                         )
 
-                        match, _ = self._compatibility_percentage(target_personality_type, personality_type)
+                        match, _ = self._compatibility_percentage(target_personality_type, personality_type, curr_weights)
 
                         self._df_files_MBTI_colleague_match.loc[
                             str(path + 1),
@@ -4351,9 +4352,9 @@ def _colleague_personality_type_match(
                         by=["Match"], ascending=False
                     )
 
-                    self._df_files_MBTI_colleague_match.index.name = self._keys_id
-                    self._df_files_MBTI_colleague_match.index += 1
-                    self._df_files_MBTI_colleague_match.index = self._df_files_MBTI_colleague_match.index.map(str)
+                    # self._df_files_MBTI_colleague_match.index.name = self._keys_id
+                    # self._df_files_MBTI_colleague_match.index += 1
+                    # self._df_files_MBTI_colleague_match.index = self._df_files_MBTI_colleague_match.index.map(str)
 
                 except Exception:
                     self._other_error(self._unknown_err, out=out)
@@ -4382,7 +4383,6 @@ def _colleague_personality_desorders(
             correlation_coefficients_disorders (pd.DataFrame): **DataFrame** c коэффициентами корреляции для расстройств
             target_scores (List[float]): Список оценок персональных качеств личности целевого человека
             personality_desorder_number (int): Количество приоритетных расстройств
-            col_name_ocean (str): Столбец с названиями персональных качеств личности человека
             threshold (float): Порог для оценок полярности качеств (например, интроверт < 0.55, экстраверт > 0.55)
             out (bool): Отображение
 
@@ -4441,6 +4441,13 @@ def _colleague_personality_desorders(
 
                         curr_weights = np.sum(curr_traits_matrix, axis=0)
 
+                        personality_type = "".join(
+                            [
+                                (name_mbti[idx_type][1] if curr_weights[idx_type] <= 0 else name_mbti[idx_type][0])
+                                for idx_type in range(len(curr_weights))
+                            ]
+                        )
+
                         for idx_type in range(len(curr_weights)):
                             idx_curr_matrix = pd_matrix[:, idx_type]
                             if curr_weights[idx_type] < 0:
@@ -4459,19 +4466,19 @@ def _colleague_personality_desorders(
                         pd_matrix = np.sum(pd_matrix, axis=1)
 
                         idx_max_values = np.argsort(-np.asarray(pd_matrix))[:personality_desorder_number]
-                        desorders = name_pd[idx_max_values]
+                        desorders = [name_pd[i] + ' ({})'.format(np.round(pd_matrix[i], 3)) for i in idx_max_values]
 
                         self._df_files_MBTI_disorders.loc[
                             str(path + 1),
-                            name_mbti.tolist()
-                            + [("Disorder" + " {}").format(i + 1) for i in range(personality_desorder_number)],
+                            ["MBTI"]
+                            + ["Disorder {}".format(i + 1) for i in range(personality_desorder_number)],
                         ] = (
-                            curr_weights.tolist() + desorders.tolist()
+                            [personality_type] + desorders
                         )
 
-                    self._df_files_MBTI_disorders.index.name = self._keys_id
-                    self._df_files_MBTI_disorders.index += 1
-                    self._df_files_MBTI_disorders.index = self._df_files_MBTI_disorders.index.map(str)
+                    # self._df_files_MBTI_disorders.index.name = self._keys_id
+                    # self._df_files_MBTI_disorders.index += 1
+                    # self._df_files_MBTI_disorders.index = self._df_files_MBTI_disorders.index.map(str)
 
                 except Exception:
                     self._other_error(self._unknown_err, out=out)
diff --git a/oceanai/modules/lab/text.py b/oceanai/modules/lab/text.py
index 452ee1a..1b86a6a 100644
--- a/oceanai/modules/lab/text.py
+++ b/oceanai/modules/lab/text.py
@@ -781,9 +781,7 @@ def __process_audio_and_extract_features(
             self._model_transcriptions = WhisperForConditionalGeneration.from_pretrained(self._path_to_transriber).to(
                 self._device
             )
-
-        if lang == self.__lang_traslate[0]:
-            self.__forced_decoder_ids = self._processor.get_decoder_prompt_ids(language=lang, task="transcribe")
+            self._model_transcriptions.config.forced_decoder_ids = None
 
         path_to_wav = os.path.join(str(Path(path).parent), Path(path).stem + "." + "wav")
 
@@ -794,71 +792,40 @@ def __process_audio_and_extract_features(
                 )
                 call_audio = subprocess.call(ff_audio, shell=True)
 
-                try:
-                    if call_audio == 1:
-                        raise OSError
-                except OSError:
+                if call_audio != 0:
                     self._other_error(self._unknown_err, last=last, out=out)
                     return np.empty([]), np.empty([])
-                except Exception:
-                    self._other_error(self._unknown_err, last=last, out=out)
-                    return np.empty([]), np.empty([])
-                else:
-                    wav, sr = torchaudio.load(path_to_wav)
-
-                    if wav.size(0) > 1:
-                        wav = wav.mean(dim=0, keepdim=True)
-
-                    if sr != 16000:
-                        transform = torchaudio.transforms.Resample(orig_freq=sr, new_freq=16000)
-                        wav = transform(wav)
-                        sr = 16000
-
-                    wav = wav.squeeze(0)
-
-                    for start in range(0, len(wav), win):
-                        inputs = self._processor(wav[start : start + win], sampling_rate=16000, return_tensors="pt")
-                        input_features = inputs.input_features.to(self._device)
-                        if lang == self.__lang_traslate[0]:
-                            generated_ids = self._model_transcriptions.generate(
-                                input_features=input_features,
-                                forced_decoder_ids=self.__forced_decoder_ids,
-                                max_new_tokens=448,
-                            )
-                        elif lang == self.__lang_traslate[1]:
-                            generated_ids = self._model_transcriptions.generate(
-                                input_features=input_features, max_new_tokens=448
-                            )
-                        transcription = self._processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-                        self.__text_pred += transcription
 
-                    return self.__translate_and_extract_features(self.__text_pred, lang, show_text, last, out)
-        else:
-            wav, sr = torchaudio.load(path_to_wav)
+        wav, sr = torchaudio.load(path_to_wav)
 
-            if wav.size(0) > 1:
-                wav = wav.mean(dim=0, keepdim=True)
+        if wav.size(0) > 1:
+            wav = wav.mean(dim=0, keepdim=True)
 
-            if sr != 16000:
-                transform = torchaudio.transforms.Resample(orig_freq=sr, new_freq=16000)
-                wav = transform(wav)
-                sr = 16000
+        if sr != 16000:
+            transform = torchaudio.transforms.Resample(orig_freq=sr, new_freq=16000)
+            wav = transform(wav)
+            sr = 16000
 
-            wav = wav.squeeze(0)
+        wav = wav.squeeze(0)
 
-            for start in range(0, len(wav), win):
-                inputs = self._processor(wav[start : start + win], sampling_rate=16000, return_tensors="pt")
-                input_features = inputs.input_features.to(self._device)
-                if lang == self.__lang_traslate[0]:
-                    generated_ids = self._model_transcriptions.generate(
-                        input_features=input_features, forced_decoder_ids=self.__forced_decoder_ids
-                    )
-                elif lang == self.__lang_traslate[1]:
-                    generated_ids = self._model_transcriptions.generate(input_features=input_features)
-                transcription = self._processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-                self.__text_pred += transcription
+        for start in range(0, len(wav), win):
+            inputs = self._processor(wav[start : start + win], sampling_rate=16000, return_tensors="pt")
+            input_features = inputs.input_features.to(self._device)
+            if lang == self.__lang_traslate[0]:
+                generated_ids = self._model_transcriptions.generate(
+                    input_features=input_features,
+                )
+            elif lang == self.__lang_traslate[1]:
+                generated_ids = self._model_transcriptions.generate(
+                    input_features=input_features, language="en"
+                )
+            transcription = self._processor.batch_decode(generated_ids, skip_special_tokens=False)
+            transcription = re.findall(r'> ([^<>]+)', transcription[0])
+            self.__text_pred += transcription[0] + ' '
 
-            return self.__translate_and_extract_features(self.__text_pred, lang, show_text, last, out)
+        self.__text_pred = self.__text_pred.strip()
+            
+        return self.__translate_and_extract_features(self.__text_pred, lang, show_text, last, out)
 
     def __load_text_model_b5(self, show_summary: bool = False, out: bool = True) -> Optional[nn.Module]:
         """Формирование нейросетевой архитектуры модели для получения оценок персональных качеств