regression_1.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 목적\n",
    "\n",
    "조개 나이 예측 -> 혹시 기후 변화 관련 ? \n",
    "\n",
    "### 2. 데이터셋\n",
    "\n",
    "이 데이터셋은 조개의 여러 특성에 관한 정보를 제공합니다. 각 열의 의미는 다음과 같습니다:\n",
    "\n",
    "1. **Sex**: 조개의 성별을 나타냅니다. 'M'은 수컷, 'F'는 암컷, 'I'는 유아기를 나타냅니다.\n",
    "2. **Length**: 조개의 가장 긴 부분의 길이를 나타냅니다.\n",
    "3. **Diameter**: 수직으로 측정한 조개의 직경을 나타냅니다.\n",
    "4. **Height**: 조개의 높이를 나타냅니다(조개껍질 포함).\n",
    "5. **Whole weight**: 조개 전체의 무게를 나타냅니다.\n",
    "6. **Shucked weight**: 조개의 살만을 제거한 무게를 나타냅니다.\n",
    "7. **Viscera weight**: 조개의 내장 무게를 나타냅니다.\n",
    "8. **Shell weight**: 조개껍질의 무게를 나타냅니다.\n",
    "9. **Rings**: 조개의 나이를 나타냅니다. 일반적으로, 링의 개수에 1.5를 더하면 조개의 나이(년)가 됩니다.\n",
    "\n",
    "각 행은 특정 조개의 위 특성을 나타냅니다. 이 데이터를 사용하여 조개의 특성과 나이 사이의 관계를 분석할 수 있습니다. 예를 들어, 회귀 분석을 사용하여 특정 특성(예: 무게, 길이 등)이 조개의 나이에 어떤 영향을 미치는지 예측할 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sklearn\n",
    "from sklearn.preprocessing import OneHotEncoder, StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import Lasso"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_reg = pd.read_csv('./csv/Regression_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1400x800 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def hist(column):\n",
    "    plt.hist(column, bins=50)\n",
    "    plt.title(f'{column.name} hist')\n",
    "    plt.show()\n",
    "\n",
    "data_reg.select_dtypes(include=[float, int]).hist(bins=30, figsize=(14,8), grid=False)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "# 수치형데이터 분포 확인\n",
    "# right skewed : column 4, 5, 6, 7\n",
    "# left skewed : column 1, 2\n",
    "# outlier 존재 : column 3\n",
    "# 타겟 데이터는 약한 right skewed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# column3 (Height) 아웃라이어 : 1.130, 0.515\n",
    "data_reg.Height.sort_values(ascending=False)[:5]\n",
    "\n",
    "# 상관계수 확인\n",
    "sns.heatmap(data_reg.iloc[:,1:].corr().abs(), annot=True, cmap='Blues')\n",
    "plt.title('Pearson Corr', fontsize=15)\n",
    "plt.show()\n",
    "\n",
    "# 전반적으로 컬럼들의 상관계수가 높다.\n",
    "# (Length, Diameter) (Whole wieght, Shucked weight)가 상관계수 높음"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EDA 및 set split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            Length     Diameter       Height  Whole weight  Shucked weight  \\\n",
      "count  4177.000000  4177.000000  4177.000000   4177.000000     4177.000000   \n",
      "mean      0.523992     0.407881     0.139516      0.828742        0.359367   \n",
      "std       0.120093     0.099240     0.041827      0.490389        0.221963   \n",
      "min       0.075000     0.055000     0.000000      0.002000        0.001000   \n",
      "25%       0.450000     0.350000     0.115000      0.441500        0.186000   \n",
      "50%       0.545000     0.425000     0.140000      0.799500        0.336000   \n",
      "75%       0.615000     0.480000     0.165000      1.153000        0.502000   \n",
      "max       0.815000     0.650000     1.130000      2.825500        1.488000   \n",
      "\n",
      "       Viscera weight  Shell weight        Rings  \n",
      "count     4177.000000   4177.000000  4177.000000  \n",
      "mean         0.180594      0.238831     9.933684  \n",
      "std          0.109614      0.139203     3.224169  \n",
      "min          0.000500      0.001500     1.000000  \n",
      "25%          0.093500      0.130000     8.000000  \n",
      "50%          0.171000      0.234000     9.000000  \n",
      "75%          0.253000      0.329000    11.000000  \n",
      "max          0.760000      1.005000    29.000000  \n",
      "     Sex  Length  Diameter  Height  Whole weight  Shucked weight  \\\n",
      "1257   I   0.430      0.34     0.0         0.428          0.2065   \n",
      "3996   I   0.315      0.23     0.0         0.134          0.0575   \n",
      "\n",
      "      Viscera weight  Shell weight  Rings  \n",
      "1257          0.0860        0.1150      8  \n",
      "3996          0.0285        0.3505      6  \n"
     ]
    }
   ],
   "source": [
    "print(data_reg.describe())\n",
    "\n",
    "print(data_reg[data_reg['Height']==0])\n",
    "\n",
    "# Height 컬럼에 최소값이 0인 것 2개 확인 -> 삭제 필요"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x1500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/34do5RWA8P/3IUpLS5mkEJEGtqgQkcGYm5tj2ouz8GP5AEx7cZjGqB8iIoAtKkRERCRhTFSIiIhIspioEBERkWQxUSEiIiLJYqJCREREksVEhYiIiCSLiQoRERFJFhMVIiIikiwmKkRERCRZTFSIiIhIspioEBERkWQxUSEiIiLJYqJCREREksVEhYiIiCSLiQoRERFJVr0SlaioKAwePBitWrWCg4MDgoKCcPbs2Vr3+/HHH+Hp6QkLCwv06dMHu3btanDARERE1HLUK1FJTk7G7NmzkZKSgoSEBFRUVGDs2LEoLi7Wuc/hw4fx7LPP4sUXX8SJEycQFBSEoKAgpKenNzp4IiIiat5M61N4z549GsubN2+Gg4MDUlNT4e3trXWf1atXY/z48YiIiAAAfPjhh0hISMB///tfrFu3roFhExERUUvQqD4qBQUFAAA7OzudZY4cOYInnnhCY924ceNw5MiRxrw0ERERtQD1alGprqqqCm+88QZGjhyJ3r176yyXm5sLR0dHjXWOjo7Izc3VuU9ZWRnKysrE5cLCQgBARUUFKioqGhqyXqhf39BxSBHrRjfWjW6VlZXi/6wfTbxutGO96Ca1utFHHA1OVGbPno309HQcPHiw0UE8KCoqCosXL66xfu/evbCystL76zVEQkKCoUOQLNaNbqybmi4XAYApUlJScJVd17TidaMd60U3qdRNSUlJo4/RoERlzpw5iI+Px4EDB9CpU6eHlnVyckJeXp7Gury8PDg5OencJzIyEqGhoeJyYWEhXFxcMHbsWNja2jYkZL2pqKhAQkIC/P39YWZmZtBYpIZ1oxvrRreTl24Bp45h2LBh6NdZ923klojXjXasF92kVjfqOyKNUa9ERRAEzJ07Fzt27EBSUhLc3d1r3Wf48OHYt28f3njjDXFdQkIChg8frnMfhUIBhUJRY72ZmZkkKh6QVixSw7rRjXVTk6mpqfg/60Y7XjfasV50k0rd6COGeiUqs2fPxpYtW7Bz5060atVK7GfSunVrWFpaAgCmT5+Ojh07IioqCgAwf/58+Pj4IDo6GpMmTcL333+PY8eOYf369Y0OnoiIiJq3eo36Wbt2LQoKCuDr6wtnZ2fx37Zt28Qyly5dQk5Ojrg8YsQIbNmyBevXr0e/fv0QExODuLi4h3bAJSIiIgIacOunNklJSTXWTZkyBVOmTKnPSxERERHxWT9EREQkXUxUiIiISLKYqBAREZFkMVEhIiIiyWKiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsJipEREQkWUxUiIiISLKYqBAREZFkMVEhIiIiyWKiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsJipEREQkWUxUiIiISLKYqBAREZFkMVEhIiIiyWKiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsJipEREQkWUxUiIiISLKYqBAREZFkMVEhIiIiyWKiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsJipEREQkWUxUiIiISLKYqBAREZFkMVEhIiIiyWKiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsJipEREQkWUxUiIiISLKYqBAREZFkMVEhIiIiyWKiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsJipEREQkWfVOVA4cOIAnn3wSHTp0gEwmQ1xc3EPLJyUlQSaT1fiXm5vb0JiJiIiohah3olJcXIx+/frh008/rdd+Z8+eRU5OjvjPwcGhvi9NRNRiqFQqJCcn48CBA0hOToZKpTJ0SEQGYVrfHSZMmIAJEybU+4UcHBzQpk2beu9HRNTSxMbGIiwsDNnZ2QCAFStWwM3NDdHR0QgODjZscERNrN6JSkP1798fZWVl6N27N95//32MHDlSZ9mysjKUlZWJy4WFhQCAiooKVFRUPPJYH0b9+oaOQ4pYN7qxbnSrrKwU/2f9ADt27MAzzzyDiRMnYtOmTcjNzYWTkxOWL1+OkJAQfP/993jqqacMHaZB8f2km9TqRh9xyARBEBq8s0yGHTt2ICgoSGeZs2fPIikpCYMGDUJZWRk2bNiAb775BkePHoWXl5fWfd5//30sXry4xvotW7bAysqqoeESkQRdLgKWnzJFeJ9KuNgYOhrDUqlUmDVrFlxdXREZGQkTk//dna+qqkJUVBQuXbqEzz77DHK53ICREtVNSUkJnnvuORQUFMDW1rZBx3jkiYo2Pj4+6Ny5M7755hut27W1qLi4uODGjRsNPlF9qaioQEJCAvz9/WFmZmbQWKSGdaMb60a3k5duIeSLY4h5eRD6dbYzdDgGlZycDH9/fyiVSgwdOrTGdZOSkgJvb28kJCTAx8fH0OEaDN9PukmtbgoLC2Fvb9+oRKXJbv1UN2TIEBw8eFDndoVCAYVCUWO9mZmZJCoekFYsUsO60Y11U5Opqan4f0uvm+vXrwO4f6u8el2or5v+/fuL5Vp6XQF8Pz2MVOpGHzEYZB6VtLQ0ODs7G+KliYgkS/25mJ6ernW7ej0/P6klqXeLSlFRES5cuCAuZ2VlIS0tDXZ2dujcuTMiIyNx9epVfP311wCAVatWwd3dHY899hju3buHDRs2YP/+/di7d6/+zoKIqBkYPXo03NzcsGTJkhpzVKn7qLi7u2P06NGGCZDIAOqdqBw7dgx+fn7icmhoKABgxowZ2Lx5M3JycnDp0iVxe3l5OcLCwnD16lVYWVmhb9+++O233zSOQUREgFwuR3R0NEJCQhAUFISIiAiUlpYiJSUFy5YtQ3x8PGJiYtiRllqUeicqvr6+eFj/282bN2ssL1iwAAsWLKh3YERELVFwcDBiYmIQFhYGb29vcb27uztiYmI4jwq1OAbpTEtERLoFBwcjMDAQiYmJ2L17NyZMmAA/Pz+2pFCLxESFiEiC5HI5fHx8UFxcDB8fHyYp1GLx6clEREQkWUxUiIiISLKYqBAREZFkMVEhIiIiyWJnWiIiCSovL8eaNWuwf/9+XLhwAXPnzoW5ubmhwyJqcmxRISKSmAULFsDa2hrh4eHYtWsXwsPDYW1tzTmpqEViiwoRkYQsWLAAy5Ytg6OjIxYvXgyFQoGysjIsWrQIy5YtAwAsXbrUwFESNR22qBARSUR5eTlWrlwJR0dHXLlyBS+88ALatm2LF154AVeuXIGjoyNWrlyJ8vJyQ4dK1GSYqBARScRnn32GyspKfPTRRzA11WzwNjU1xQcffIDKykp89tlnBoqQqOkxUSEikojMzEwAQEBAgNbt6vXqckQtARMVIiKJ6Nq1KwAgPj5e63b1enU5opaAiQoRkUS8/vrrMDU1xbvvvovKykqNbZWVlXjvvfdgamqK119/3UAREjU9JipERBJhbm6ON998E3l5eejUqRM2bNiAW7duYcOGDejUqRPy8vLw5ptvcj4ValE4PJmISELUQ49Xrlyp0XJiamqKiIgIDk2mFoctKkREErN06VIUFxdj+fLlmDhxIpYvX47i4mImKdQisUWFiEiC5HI5+vXrh2vXrqFfv36Qy+WGDonIINiiQkQkMbGxsejatSv8/f2xYsUK+Pv7o2vXroiNjTV0aERNjokKEZGExMbGYvLkycjPz9dYn5+fj8mTJzNZoRaHiQoRkUSoVCq89tprAIB79+5pbFMvz5o1CyqVqsljIzIUJipERBKRlJSE69evP7RMfn4+kpKSmiYgIglgokJEJBH79u0Tf544cSKUSiW2bt0KpVKJiRMnai1H1Nxx1A8RkUT8/vvvAAB3d3f89NNPUKlUuHnzJoYOHYqffvoJXbt2RXZ2tliOqCVgokJEJBHqfiiWlpYoLy/Hp59+iv379+PChQuYPXs2LC0tNcoRtQRMVIiIJMLV1RWHDh3CX3/9BSsrKwiCAADYtWsXIiIixGVXV1dDhknUpNhHhYhIImbMmCH+rE5KtC1XL0fU3DFRISKSiNGjR4s/y2QyjW3Vl6uXI2rumKgQEUnE559/Lv78sBaV6uWImjsmKkREEpGZmSn+rFAoNLZZWFhoLUfU3DFRISKSCDc3N/F/e3t7jW3t2rUTO9GqyxG1BBz1Q0QkEX369AEAZGdn19h29erVGuWIWgK2qBA9YiqVCsnJyThw4ACSk5P5nBbS6cHp8x0cHNC1a1c4ODg8tBxRc8YWFaJHKDY2FmFhYeJfyCtWrICbmxuio6MRHBxs2OD0IOtGMYrLKht1jMzrxeL/pqYN/0iyVpjC3d66UbEY2qVLlzSW8/PzazxFWVs5ouaMiQrRIxIbG4uQkBAEBATgm2++wZUrV9CpUycsXboUISEhiImJMepkJetGMfyWJ+nteGExpxp9jMRwX6NOVmJiYsSfzc3N8dhjj6G0tBSWlpY4ffo0ysvLxXKRkZGGCpOoSTFRIXoEVCoVwsLCEBAQgLi4OI1ntsTFxSEoKAjh4eEIDAyEXC43dLgNom5JWTW1PzwcbBp+nNIyxCcdQYDvcFhbKmrfQYsL+UV4Y1tao1t3DO3mzZvizzKZDCdOnBCXq48Cql6OqLljokL0CCiVSmRnZ2Pr1q0wMTHR6JdiYmKCyMhIjBgxAkqlEr6+voYLVA88HGzQu2PrBu9fUVGB3PaAl2tbmJmZ6TEy41N9UreysjKNbdWXH5wMjqg5Y2daokcgJycHANC7d2+t29Xr1eWIgPtPTdZnOaLmgIkK0SPg7OwMAEhPT9e6Xb1eXY4IAKysrPRajqg5YKJC9AiMHj0abm5uWLJkCaqqqjS2VVVVISoqCu7u7nxmC2koLi7Wazmi5oCJCtEjIJfLER0djfj4eAQFBSElJQWlpaVISUlBUFAQ4uPjsXz5cqPtSEuPxrVr1/Rajqg5YGdaokckODgYMTExCAsLg7e3t7je3d3d6Icm06PRoUMHnDt3rk7liFoKJipEj1BwcDACAwORmJiI3bt3Y8KECfDz82NLCmnVuXNnvZYjag6YqBA9YnK5HD4+PiguLoaPjw+TFNLpwIEDei1H1BywjwoRkUQUFBTotRxRc8BEhYhIIuzs7PRajqg5YKJCRCQRLi4uGsvt27eHg4MD2rdv/9ByRM0Z+6gQEUmEjY3mM5OuX79ep3JEwP1njCUnJ+PAgQOwtrZuNh33692icuDAATz55JPo0KEDZDIZ4uLiat0nKSkJXl5eUCgU8PDwwObNmxsQKhFR83br1i29lqOWIzY2Fh4eHvD398eKFSvg7+8PDw8PxMbGGjq0Rqt3olJcXIx+/frh008/rVP5rKwsTJo0CX5+fkhLS8Mbb7yBl156Cb/++mu9gyUias7Mzc31Wo5ahtjYWISEhKBPnz5QKpXYunUrlEol+vTpg5CQEKNPVup962fChAmYMGFCncuvW7cO7u7uiI6OBgD07NkTBw8exMqVKzFu3Lj6vjwRUbOVl5en13LU/KlUKoSFhSEgIABxcXFQqVS4efMmhg4diri4OAQFBSE8PByBgYFGexvokXemPXLkCJ544gmNdePGjcORI0ce9UsTERmV8vJyvZaj5k+pVCI7OxsLFy6EiYnmV7qJiQkiIyORlZUFpVJpoAgb75F3ps3NzYWjo6PGOkdHRxQWFqK0tBSWlpY19ikrK0NZWZm4XFhYCACoqKhARUXFow24FurXN3QcUsS60a051k1lZaX4f2POSx91o69YDE39Wac2YMAAWFlZoaSkBCdOnNAoZ8zn2VjN8f3UUJcvXwYA9OjRQ+M7Uv1/jx49xHKGqC99vKYkR/1ERUVh8eLFNdbv3btXMo83T0hIMHQIksW60a051c3lIgAwxcGDB3FRD4NQGlM3+o7FUKr/gQZAIzl5sNyuXbuaIiRJa07vp4a6ePEiAOCLL74QkxLgf3WTkZEhljPENVNSUtLoYzzyRMXJyanG/dS8vDzY2tpqbU0BgMjISISGhorLhYWFcHFxwdixY2Fra/tI461NRUUFEhIS4O/vDzMzM4PGIjWsG92aY92cvlaI5adSMGrUKDzWoeHvS33Ujb5iMTQbGxuxVcXMzAy9evXCvXv3YGFhgb/++kv869TGxgYTJ040ZKgG1RzfTw01btw4fPnllzhw4ADmz58PlUol1o1cLscXX3wBd3d3hIeHG6SPyoOthA3xyBOV4cOH18jiEhISMHz4cJ37KBQKKBSKGuvNzMwkc1FKKRapYd3o1pzqxtTUVPxfH+fUmLrRdyyG4unpiWvXrgG4/2V88uRJneWM+Tz1pTm9nxrKzMwM0dHRCAkJwZQpUxAREYHS0lKkpqZi2bJl2LVrF2JiYmBhYWGw+Bqr3olKUVERLly4IC5nZWUhLS0NdnZ26Ny5MyIjI3H16lV8/fXXAIDXXnsN//3vf7FgwQK88MIL2L9/P3744Qf88ssvjQ6eiMhYlZSUiM3yak899RT2799f675PPfUUjh8/Li57enpK5rY4Nb3g4GDExMQgLCwM3t7e4np3d3fExMQgODjYgNE1Xr0TlWPHjsHPz09cVt+imTFjBjZv3oycnBxcunRJ3O7u7o5ffvkFb775JlavXo1OnTphw4YNHJpMRC1aRkYGBg4c2KB9586dq7GcmpoKLy8vfYRFRio4OBiBgYFITEzE7t27MWHChGYzM229ExVfX18IgqBzu7ZZZ319fXV2CiMiaok8PT2RmppaY/3+/fsRERGhc79ly5ZhzJgxNY5FJJfL4ePjg+LiYvj4+DSLJAWQ6KgfIqLmzsrKSmsriJeXF7p06YI333xTo3Xa1dUVK1asMPpmfKL64tOTiYgkJjg4GH///Te+2BoH+ycj8MXWOGRmZjJJoYeq/lDC5ORkqFQqQ4ekF0xUiIgkSC6XY9DwUbDu5YNBw0c1m2Z8ejRiY2PRpUsXjYcSdunSxeif8wMwUSEiIjJqsbGxmDx5sjhLrdrly5cxefJko09WmKgQEREZKZVKhZkzZwIAHBwcsG7dOmzatAnr1q2Dg4MDAGDmzJlGfRuIiQoREZGR2rdvHwoLC2FnZ4crV67ghRdeQNu2bfHCCy/gypUrsLOzQ2FhIfbt22foUBuMiQoREZGR+uabbwAAixcvhkwm0+hMK5PJsGjRIo1yxojDk4mIiIxUUVERAODatWvw8PBAdnY2AGDFihVwc3PDM888o1HOGLFFhYiIyEiNGjUKABAVFYXevXtDqVRi69atUCqV6N27N/7zn/9olDNGTFSIiIiM1Ouvvy7+XFVVJc4cLwgCqqqqtJYzNrz1Q0REZKSOHj0q/rxnzx7s2rVLXK4+987Ro0fh6+vblKHpDVtUiIiIjFROTg4AYP78+ZDJZBrbZDIZ5s+fr1HOGDFRISIiMlLOzs4AACcnJ3Ts2FFjW4cOHeDo6KhRzhjx1g8REZGRGj16NBwcHBAZGYlJkyYhPDwc586dQ/fu3fHrr79i4cKFcHBwwOjRow0daoMxUSEiIjJi6g60+/fvxy+//CKut7S0NFRIesVEpZqSkhJkZGQ8tExRaRkOn8pEW/tjsLFUPLSsp6cnrKys9BkiERGRSKlU4vr16zX6pwD3+6jIZDLk5+dDqVQabWdaJirVZGRkYODAgXUqu7QOZVJTU+Hl5dW4oIgkqkx1DyYWV5FVeBYmFjYNPk5lZSWuVV7DmVtnYGrasI+krMIimFhcRZnqHoDWDY6FyNhcvXoVANC/f3/cvHkTly5dErfZ29ujXbt2OHHihFjOGDFRqcbT0xOpqakPLXM25w5CfzyFFVP6oIdzm1qPR9RcXSu+CGv3NVj4u36O99mezxq1v7U7cK24PwbCUT8BkSSpVCpxmnhra2v4+flpDMNtaa5fvw4AOHHiBAICAjT6qOzduxfx8fEa5YwRE5VqrKysam0BMbl4EwplKXr27of+ru2aKDIi6elg7YrirLlYPbU/ujo0rkXl0MFDGDlqZINbVDLzizB/Wxo6+Lk2OA6SvtjYWISFhdWYJj46OhrBwcGGDc5A2rW7/z1ka2uL9PR0MTEBADc3N9ja2qKwsFAsZ4yYqBBRgyjkFqi61xHutj3Qq13Db7dUVFQgyzQLPe16wszMrEHHqLpXgKp716GQWzQ4DpK22NhYhISEICAgAN988w2uXLmCTp06YenSpQgJCUFMTEyLTFZu3rwJACgsLISlpSXWrl0LCwsL3Lt3D++//z4KCws1yhkjJipERCRpKpUKYWFhCAgIQFxcHFQqFW7evImhQ4ciLi4OQUFBCA8PR2BgYIu7DVS9RUWhUGDWrFniNldX12bRosIJ34iISNKUSiWys7OxcOFCmJhofm2ZmJggMjISWVlZUCqVBorQcNQtJXfv3kWvXr3Qu3dv2NnZoXfv3ujZsyfu3r2rUc4YsUWFiIgkTT39e+/evbVuV6835mniG6p9+/YAAAsLC+zZs0dcf+vWLaSnp8PS0hKlpaViOWPEFhUiIpI09fTv6enpWrer1xvzNPENpZ42v7S0FADQqVMndOvWDZ06ddJY/+D0+saEiQoREUna6NGj4ebmhiVLlqCqqkpjW1VVFaKiouDu7m7U08Q31IABAzSWr1y5gvPnz+PKlSsPLWdMmKgQEZGkyeVyREdHIz4+HkFBQUhJSUFpaSlSUlIQFBSE+Ph4LF++vMV1pAWA559/Xq/lpIh9VIiISPKCg4MRExODsLAweHt7i+vd3d1b7NBkALhw4YJey0kRExUiIjIKwcHBCAwMRGJiInbv3o0JEya0+Jlp1Q8k1Fc5KWKiQkRERkMul8PHxwfFxcXw8fFp0UkKcH/22dOnT9epnLFiHxUiIiIjpR7Vo69yUsREhYiIyEg9OAqqseWkiIkKEREZjepPT05OToZKpTJ0SAaVlZWl13JSxESFiIiMQmxsLDw8PODv748VK1bA398fHh4eiI2NNXRoBqOeIl9f5aSIiQoREUme+unJffr0gVKpxNatW6FUKtGnTx+EhIS02GSlJdz64agfqpOSkhJkZGQ8tExRaRkOn8pEW/tjsLFUPLSsp6cnrKys9BkiETVTfHqybg8+pLGx5aSIiQrVSUZGBgYOHFinskvrUCY1NRVeXl6NC4qIWgT105O3bt0KExMTjX4p6qcnjxgxAkqlEr6+voYL1ADYokL0fzw9PZGamvrQMmdz7iD0x1NYMaUPeji3qfV4RER1wacn68YWFaL/Y2VlVWsLiMnFm1AoS9Gzdz/0d23XRJERUXNX/enJgwcPFkf9WFtbw8/Pr8U8PVnbLXiF4uG32auXO378uMY6Y7kF36ISlawbxSguq2zUMTKvF4v/m5o2rvqsFaZwt7du1DGIiJo79dOT586dixs3biA7OxsAsGLFCri5ucHe3r5FPD25PrfgH5STk1NjX2O5Bd9iEpWsG8XwW56kt+OFxZzSy3ESw32ZrBARPYRcLseUKVOwbNkytG/fHiEhIbh9+zbatm2L5ORkZGdnIyIiotl3pNV2Cz4lJQWzZ8+udd9PP/0Uw4YNq3E8Y9BiEhV1S8qqqf3h4WDT8OOUliE+6QgCfIfDupaRLQ9zIb8Ib2xLa3QLDxFRc6dSqfDjjz/C0dEReXl5iImJ0dju6OiImJgYREVFNetkRdst+H79+mHhwoUoKCjQuV/r1q3x6quvGm3dtJhERc3DwQa9O7Zu8P4VFRXIbQ94ubaFmZmZHiMjIiJt1KN+gPudQquPYDExMUFeXp5YrqWN+pHL5di4cSMmT56ss8zGjRuNNkkBOOEbERFJ3OXLl8Wfx48fj9WrV2POnDlYvXo1xo8fr7VcSxIcHIzt27fD1dVVY72bmxu2b9+O4OBgA0WmHy2uRYWIiIzL4cOHAQBOTk5IT0/Hrl27xG2dO3eGk5MTcnNzcfjwYfzrX/8yVJgGFRwcjMDAQGz6MR6RWw4h6rmRmDklwKhbUtSYqBARkaSp50fJzc2FTCbT2Hb58mUIgqBRrqWSy+UYNHwUrNNMMWj4sGaRpABMVIiISOJsbP43AEIul8PBwQElJSWwsrJCfn4+Kisra5Sj5oOJCtEjVv2x9OoJqprLXzpETeGxxx4Tf66srMS1a9cAAHfu3NFZjpqPFpOolKnuwcTiKrIKz8LEouFZd2VlJa5VXsOZW2caNeFbVmERTCyuokx1D0DDRyGRtMXGxiIsLKzGBFXR0dFG38GNqKmcPn1ar+XIuLSYROVa8UVYu6/Bwt/1c7zP9nzW6GNYuwPXivtjIBz1EBFJjfqx9AEBAfjmm29w5coVdOrUCUuXLkVISAhiYmKYrBDVwe3bt/VajoxLgxKVTz/9FMuWLUNubi769euHNWvWYMiQIVrLbt68GTNnztRYp1AocO/evYa8dIN1sHZFcdZcrJ7aH10bMeFbZWUlDh08hJGjRjaqRSUzvwjzt6Whg59r7YXJ6PCx9ET6c+pU3WYCr2s5Mi71/qbdtm0bQkNDsW7dOgwdOhSrVq3CuHHjcPbsWTg4OGjdx9bWFmfPnhWXH+y13RQUcgtU3esId9se6NWucRO+ZZlmoaddz0ZN+FZ1rwBV965DIbdo8DFIuvhYeiL9UfdJ0Vc5Mi71nvBtxYoVePnllzFz5kz06tUL69atg5WVFTZu3KhzH5lMBicnJ/GfoyNvdVDzxsfSE+lP9URfH+XIuNSrRaW8vBypqamIjIwU15mYmOCJJ57AkSNHdO5XVFQEV1dXVFVVwcvLC0uWLHlo7+yysjKUlZWJy4WFhQDut2ZUVFTUJ2SRevhaZWVlg4+hjqH6/w2lr3ikpDmeU0O1b98eAJCWloahQ4fWuG7S0tLEcsZaV1J6T0nx2su+WYzissZ9cZ7LLdD4v6GsFXK4tTPeh59WnzZf2xT61bdJ5fdvKFJ7L+gjhnolKjdu3IBKparRIuLo6IiMjAyt+/To0QMbN25E3759UVBQgOXLl2PEiBE4ffo0OnXqpHWfqKgoLF68uMb6vXv3wsrKqj4hiy4XAYApDh48iIt6GGqfkJDQqP31HY8UqM8pJSUFV9MNHY1hqVQqODg4IDQ0FJGRkTAxud94mZCQgKqqKkRFRcHR0RGFhYUas2waEym9p6T2fsovBf6dpr+xCgt2nGn0Md7pXwkHSz0E0wTKyspw5coVcdnGxkb8g7Wqqgr29vZoa++I2zfycOPGDY1ya9as0ThWp06doFA0/AGyxkZqn8MlJSWNPsYjH/UzfPhwDB8+XFweMWIEevbsic8//xwffvih1n0iIyMRGhoqLhcWFsLFxQVjx46Fra1tg+I4fa0Qy0+lYNSoUXisQ8OOAdzPDhMSEuDv79+oPir6ikdf9PHXX1luAXDqDBw8+sDVqXFDro39L0Dg/l80zzzzDL788kuEhYUhLy8Pjo6OiI6OxrFjx/D999/jySefNHSYDSal95TU3k+nrxUCaSlYHtIHHu0bfh0X3yvDHuUfGD96MKwtGvZle+F6McJjTmHwcGnUTV2cOHECU6dO1bn9xo0bGgmKWmFhIcLCwjTWHT16FAMGDNB7jFJ18tIt4NQxDBs2DP062xk6HDHBbIx6JSr29vaQy+XikyrV8vLy4OTkVKdjmJmZYcCAAbhw4YLOMgqFQmsGbGZm1uAPMvUIHVNTU7089bgxsTyKeBoj60Yx/Fcd0tvx9PHXHwAkhvvC3d54k5Wnn34apqamCAsLw5gxY8T17u7uzWJospTeU1J6P6njAABP59aNflr7jQxgSJf2zaZu6qJ3795ITU0Vl1NSUjB79uxa9/v0008xbNgwjXWenp5Gc976ILXftz5iqFeiYm5ujoEDB2Lfvn0ICgoCcL8Zbt++fZgzZ06djqFSqXDq1ClMnDix3sHSo1Fcdv+e5qqp/eHRiKHbxaVliE86ggDf4bC2bHhT64X8IryxLU2My5ipHxSWmJiI3bt3Y8KECZyZlqgWVlZW8PLyEpf79euHyMjIh/51bmtri1dffZXvrWao3rd+QkNDMWPGDAwaNAhDhgzBqlWrUFxcLM6VMn36dHTs2BFRUVEAgA8++ADDhg2Dh4cH7ty5g2XLluHixYt46aWX9Hsm1GgeDjaN/usvtz3g5dpWEpm8VMjlcvj4+KC4uBg+Pj78ICWqJ7lcjk2bNmHy5Mk6y2zatInvrWaq3onK1KlTcf36dbz33nvIzc1F//79sWfPHrGD7aVLl8SOg8D9mQJffvll5Obmom3bthg4cCAOHz6MXr166e8s6qC04n7/i/Srjes9X1xahmPXAaeLtxvdakBERHUTHByM7du3IzQ0FBcvXhTX85EUzV+DOtPOmTNH562epKQkjeWVK1di5cqVDXkZvcr8v8Tg7Vh9zFxoim8u/KGH4wDWihbzFANqZqSU/DPxbxnUt1I3/RiPyC2HEPXcSMycEsCWlGauxXxLjn3sfmffrg42sDRr+EV9NqcAYTGnEB3SBz2cGzuyxdSoO4tSyybF5J+Jf/Mnl8sxaPgoWKeZYtDwYUxSWoAW8662szbHM0M6N/o46sl0ura3blR/Dinhk6WpIaSW/DPxJ2qeWkyiQrrxydLUEEz+iagpMFEhPlmaiIgki4kK8cnSREQkWfV+ejIRERFRU2GiQkRERJLFRIWIiIgki4kKERERSRYTFSIiIpIsjvohSU2FDnA6dCIi+h8mKiTJqdABTodORERMVAjSmwod4HToZNyk9FgKPpLCuGTdKEZxWWWD98+8Xiz+35iJNwHpfA4zUSFOhU6kZ1J7LAUfSWEcsm4Uw295kl6OFRajjxZyIDHc1+DJChMVIiI9k9JjKfhICuOhbklZNbU/PBp43RSXliE+6QgCfIc3uq/gG9vSGtW6oy9MVIiI9ExKj6XgIymMj4eDTYNbpSsqKpDbHvBybduoR5lICYcnExERkWQxUSEiIiLJYqJC9IiVlpZi3rx5eP/99zFv3jyUlpYaOiQiIqPBRIXoEQoKCoKVlRXWrVuHtLQ0rFu3DlZWVggKCjJ0aERERoGJCtEjEhQUhJ07d8Lc3BwLFizA2rVrsWDBApibm2Pnzp1MVoiI6oCjfogegdLSUjFJuXv3LmQyGXbt2oUXX3wRH374IVq1aoWdO3eitLQUlpaWhg6XqElxUjOqDyYqRI9AREQEACA0NBTm5uaoqKgQt5mbm+ONN97A0qVLERERgf/+97+GCpOoyXFSM6ovJipEjVRSUoKMjAyNdampqQCAYcOG4fjx4ygqLcPhU5loa38MNpYKDBs2TCx3/PhxjX09PT1hZWXVNMETNTFOakb1xUSlHq5evQqfvo+h8G4RfNba4K+/TqNjx46GDosMLCMjAwMHDtS67cF+KEsf2J6SklJj39TUVHh5eekxQiLp4aRmNenjGVH6eD4UIK1nRDFRqSOFQoHy8nJxubCwAJ06dYK5uTnKysoMGBkZmqenp9iColZaWopRo0bBzMwMBw4cQNbNEoT+eAorpvSBezsreHt7o6KiAgcPHqzRR8XT07MpwyciidDnM6Ia+3woQDrPiGKiUgcPJinVlZeXQ6FQMFlpwaysrLS2gAQGBmLnzp3w8fHBcy+8BplZL+yN34ktG9ehoqICgYGBGDlypAEiJiIp0sczovTxfChAWs+IYqJSjba+BlevXtWZpKiVl5fj559/rnEbiH0NWra4uDhxiPLmdZ8AADb/37bAwEDExcUZKjQikiB9PCNKH8+HAqT1jCgmKtU8rK9Bbf7xj3/UWMe+BhQXF4fS0lI8/+oc/KQ8gX+MHoDNn/+XQ5KJiOqIiUo12voa1CdxeXBf9jUgALC0tETkh0txdG0KImcNY5LSApRWqAAA6VcLGnWc4tIyHLsOOF283eDRLRfyixoVA5GhMVGpRldfg7pqya0naWlpGDBgAABgwMfAiRMn0L9/f8MGRWQgmf+XHLwdq495PkzxzYU/Gn0UawU/7sk48cqlRpPJZDXWqZMWQRCaOhwigxv7mBMAoKuDDSzN5A0+ztmcAoTFnEJ0SB/0cG74EFEpzb7KIbhUX0xUqFG0JSkPbjf2ZKWx030DnPK7pbGzNsczQzo3+jiVlfevu67trRs854jUcAgu1RcTFaoTbSOi0tPT67Tv119/jd69e2usM5YRUfqc7hvglN9EHIJL9cVEheqkMSOiZsyYUWOdsYyI0sd03wCn/CZS4xBcqi8mKrVo3749rl+/XqdyzVlLHRGlvp8ut2jf4PvpAGBpWokOba/BslUuTBrxF6DcgvfUiahlYaJSi7pm683peRPatNQRUfq8nw7wnjoR6aaPYe36GNIOSGtYOxOVWrRt2xbXrl2rUzlqfvRxPx3gPXUiqp3+hrXrZ0g7II1h7YaPQOJGjhyJ06dP16kcNT9VVWaoutcRxXedUGXb8FstpaVluHa7A0rvOjXqrxzVvSLeUydqpvQxrF1fQ9oB6YwwZKJSi1GjRmH9+vV1KkfNjxQn7gKk8VcOEemXPoa1N8ch7fy0q4WLi4tey5FxkdrEXYB0/sohagj2w6D6YqJSi9GjR8PBwQH5+fk6yzg4OGD06NFNGJU02NjYoKio9je6jU3D+3YYGifuItIv9sOg+uJvpw7UM6tOnDgRXbp0wblz59C9e3f8/fff2LVrl4GjM5xBgwYhKSmpTuWIiAD2w6D6Y6JSC6VSievXryMqKgqff/65mJjs3bsX7u7uWLJkCRYuXAilUglfX1/DBtvEFixYUKdEZcGCBY8+GAm7desWQsaOwqVLVxGyoyN+P3IIdnZ2hg6LyCDYD4Pqy8TQAUhdTk4OAGDOnDm4cOECEhISEBoaioSEBJw/fx5z5szRKNeSPP7443ot1xw5OTmhXbt2yDyXAeHeXWSey0C7du3g5ORk6NCIiIwCE5VaODs7A7j/XBu5XA4fHx94e3vDx8cHcrlcfN6NulxLcvjwYb2Wa26cnJyQl5endVteXh6TFSKiOmCiUovRo0fDzc0NS5YsQVVVlca2qqoqREVFwd3dvUV2plW3In377bfo3FmzKdfV1RXffvutRrmW5NatWzqTFLW8vDzcunWriSIiIjJO7KNSC7lcjujoaISEhCAoKAgREREoLS1FSkoKli1bhvj4eMTExEAub/jQVWOlbkXq2rUr/v77byQmJmL37t2YMGEC/Pz88Pvvv2uUa660PVl68uTJddp34MCB2L59u8Y6Y3myNBFRU2hQi8qnn34KNzc3WFhYYOjQoeIXki4//vgjPD09YWFhgT59+hjdSJng4GDExMTg1KlT8Pb2xrPPPgtvb2+kp6cjJiYGwcHBhg7RIKq3NslkMo3bYjKZrMW0NqmfLF39X3Z2dp32zc7OrrHvg0kPEVFLVu8WlW3btiE0NBTr1q3D0KFDsWrVKowbNw5nz56Fg4NDjfKHDx/Gs88+i6ioKAQEBGDLli0ICgrC8ePH0bt3b72cRFMIDg5GYGBgjVaDltiSosbWpvtqe7K0nZ0dXnzpFRRDAWuU4csN6zVu+Rjrk6WJiJqEUE9DhgwRZs+eLS6rVCqhQ4cOQlRUlNbyTz/9tDBp0iSNdUOHDhVeffXVOr9mQUGBAEAoKCiob7h6V15eLsTFxQnl5eWGDkUytm/fLri5uQkAxH/u7u7C9u3bDR2awVSvi9u3b2tcN7dv39bY3tKdyL4huL4VL5zIvmHoUCSHdaMd60U3qdWNPr6/69WiUl5ejtTUVERGRorrTExM8MQTT+DIkSNa9zly5AhCQ0M11o0bNw5xcXE6X6esrAxlZWXicmFhIQCgoqICFRUV9QlZ79Svb+g4pOTJJ5/ExIkTkZSUhISEBPj7+8PX1xdyubzF1pOJiYnY+bpt27YYNGgQJk6ciI8++gjHjh3TKNec66ikpARnz559aJlzOQUoy72A9DRzlOc9fE6MHj16NJv+O/qsm+ZUL0DtdcNrRjep1Y0+Pt/qlajcuHEDKpUKjo6OGusdHR113lfPzc3VWj43N1fn60RFRWHx4sU11u/du1cyF1xCQoKhQ5Akb29vlJWV4ddffzV0KAbl5OSEa9euicvHjh3TSFCqlzO2Plv1kZmZibCwsDqV/ddXtZeJjo5G165dGxmVNOizbppTvQB1rxteM7pJpW5KSkoafQxJjvqJjIzUaIUpLCyEi4sLxo4dC1tbWwNGdj87VLcamJmZGTQWqWHd/M+cOXOwcOHCOpWbOHFiE0RkGCUlJbU+WbyotAy/Kv/AuNGDYVPLA+aa21/H+qqb5lQvQO11w2tGN6nVjfqOSGPUK1Gxt7eHXC6vMT/Ewyav0jbpVW2TXSkUCigUNSvYzMxMMl+AUopFalg3QFhYGN555x3xOVHayGQyhIWFNeu6at26NYYMGfLQMhUVFbh75xZGjxjWrOviQawb3WqrG9aLblKrG33EUK/hyebm5hg4cCD27dsnrquqqsK+ffswfPhwrfsMHz5cozxw/7aJrvJEzYG5uTnCw8MfWiY8PBzm5uZNFBERkXGq962f0NBQzJgxA4MGDcKQIUOwatUqFBcXY+bMmQCA6dOno2PHjoiKigIAzJ8/Hz4+PoiOjsakSZPw/fff49ixY1i/fr1+z4RIYpYuXQoAWLFiBVQqlbje1NQUb775pridiIh0q3eiMnXqVFy/fh3vvfcecnNz0b9/f+zZs0fsMHvp0iWYmPyvoWbEiBHYsmUL3n33XSxcuBDdunVDXFycUc2hQtRQS5cuxUcffYQ1a9Zg//79GDNmDObOncuWFCKiOmpQZ9o5c+aITw1+UFJSUo11U6ZMwZQpUxryUkRGz9zcHPPmzYOHhwcmTpwoifvGRETGgg8lJCIiIsliokJERESSxUSFiIiIJIuJChEREUkWExUiIiKSLCYqREREJFlMVIiIiEiymKgQERGRZDFRISIiIslq0My0TU39BFp9PC66sSoqKlBSUoLCwkLOMPoA1o1urBvdWDe6sW60Y73oJrW6UX9vP+xJ8rUxikTl7t27AAAXFxcDR0JERET1dffuXbRu3bpB+8qExqQ5TaSqqgrXrl1Dq1atIJPJDBpLYWEhXFxccPnyZdja2ho0Fqlh3ejGutGNdaMb60Y71otuUqsbQRBw9+5ddOjQQeOBxfVhFC0qJiYm6NSpk6HD0GBrayuJi0CKWDe6sW50Y93oxrrRjvWim5TqpqEtKWrsTEtERESSxUSFiIiIJIuJSj0pFAosWrQICoXC0KFIDutGN9aNbqwb3Vg32rFedGuOdWMUnWmJiIioZWKLChEREUkWExUiIiKSLCYqREREJFlMVAzg+eefR1BQkKHDgEwmQ1xcnKHDaLbc3NywatWqOpfPzs6GTCZDWlraI4tJG31cB76+vnjjjTf0Eo8+6KrLh53r5s2b0aZNm0a/dn1/73XR1PXbv3//es998SjO29AaUu8ymeyRvKeaun4beu6P4julWScqhk4IDPXF8/zzz4tvFjMzMzg6OsLf3x8bN25EVVWVWC4nJwcTJkxo0ti0ef/999G/f39DhyHSdd0kJSVBJpPhzp07dTrOH3/8gVdeeUWvsen6Ml23bh1atWqFyspKcV1RURHMzMzg6+urUVZ9HpmZmXqNzdCuX7+OWbNmoXPnzujRowfat2+PBQsW4NChQ3p7DUN/pjTWk08+ifHjx2vdplQqIZPJ8Oeff+KXX37BiRMn9Prahvo8bIzY2Fh8+OGHGuuqX2cKhQJOTk4YN25cna+z+n6OGIq2c2+shp67UcxMS/U3fvx4bNq0CSqVCnl5edizZw/mz5+PmJgY/PTTTzA1NYWTk5Ohw9Sr8vJymJubGzoMUfv27Zvstfz8/FBUVIRjx45h2LBhAO5/8Tg5OeHo0aO4d+8eLCwsAACJiYno3Lkzunbt2mTxNYXJkyejvLwcX331Fbp06YK8vDzs27cPN2/eNHRokvHiiy9i8uTJuHLlSo3Zvjdt2oRBgwahb9++BoruPpVKBZlM1uDp1vXJzs6uxrqWcp1pO3dDMfyVYCDp6emYMGECbGxs4OjoiH/961+4ceOGuN3X1xfz5s3DggULYGdnBycnJ7z//vsax8jIyMCoUaNgYWGBXr164bffftNo+nJ3dwcADBgwADKZrMZftsuXL4ezszPatWuH2bNno6KiQm/np870O3bsCC8vLyxcuBA7d+7E7t27sXnzZgA1m+neeustdO/eHVZWVujSpQv+3//7fxoxqVs+Nm7ciM6dO8PGxgavv/46VCoVli5dCicnJzg4OODf//63Rix37tzBSy+9hPbt28PW1hZjxozByZMnAdxvIVi8eDFOnjwptgKp43vYftXj2bBhA9zd3cUv4qZy8OBBjB49GpaWlnBxccG8efNQXFwsbn+wqba260Xt77//hp+fH6ysrNCvXz8cOXIEwP2/RmbOnImCggKxrtTXZI8ePeDs7IykpCTxOElJSQgMDIS7uztSUlI01vv5+Wm85o0bN/DUU0/BysoK3bp1w08//aSxPTk5GUOGDIFCoYCzszPefvttjdabB5WVlSE8PBwdO3aEtbU1hg4dqhHbg8LDwxEQECAur1q1CjKZDHv27BHXeXh4YMOGDeLyhg0b0LNnT1hYWKBbt25QKpX4+OOP4efnB0EQMHToUEyYMAH/+Mc/AEA8pylTpqB9+/ZQKBSQyWTYsmWLeMzy8nLY2NigZ8+esLGxwfjx47Fx40axrr/66ivs3LlTrH9zc3PY29vjqaee0nluGzZsQJs2bbBv3z4AtX/2FBcXY/r06bCxsYGzszOio6N1HhsACgoKIJfLcezYMQD3n41mZ2cnJqwA8O2338LFxQUBAQFo3749Vq9ejaeffhpt2rSBnZ0dJk2ahB9++AEvvvgigJq3fnbt2oV27dqJCYS7uzuGDRsm3hr4+eefkZOTg4iICFhYWMDU1BSdO3fG+vXrxWtB1+ehupXwp59+Qq9evaBQKHDp0iX88ccf8Pf3h729PVq3bg0fHx8cP35cZz2kp6fDxMQE169fBwDcunULJiYmeOaZZ8QyH330EUaNGqWxT23fA9Vvf2RkZECpVOLEiRN44YUXcOjQITz99NOwtLQUrzO1xYsXQy6Xw8TEBB06dMBPP/2E7Oxs8b3Xtm1bjVbvB1+7Ppri3HNycjBp0iRYWlrC3d0dW7Zs0Xo7StdnibZzf/755+t0fi0yUblz5w7GjBmDAQMG4NixY9izZw/y8vLw9NNPa5T76quvYG1tjaNHj2Lp0qX44IMPkJCQAOB+1h8UFAQrKyscPXoU69evxzvvvKOx/++//w4A+O2335CTk4PY2FhxW2JiIjIzM5GYmIivvvoKmzdvFr+gH5UxY8agX79+GnFU16pVK2zevBl//fUXVq9ejS+++AIrV67UKJOZmYndu3djz5492Lp1K7788ktMmjQJV65cQXJyMj7++GO8++67OHr0qLjPlClTkJ+fj927dyM1NRVeXl54/PHHcevWLUydOhVhYWF47LHHkJOTg5ycHEydOrXW/dQuXLiA7du3IzY2tkmblDMzMzF+/HhMnjwZf/75J7Zt24aDBw9izpw5WsvX5XpRe+eddxAeHo60tDR0794dzz77LCorKzFixAisWrUKtra2Yl2Fh4eL+/n5+SExMVFcTkxMhK+vL3x8fMT1paWlOHr0aI1EZfHixXj66afx559/YuLEiZg2bZpYz1evXsXEiRMxePBgnDx5EmvXrsWXX36Jjz76SGf9zJkzB0eOHMH333+PP//8E1OmTMH48eNx/vx5reV9fHxw8OBBqFQqAPcTI3t7ezG5uXr1KjIzM8Uvt++++w7vvfce/v3vf+PMmTNYsmQJAGDJkiUoKyurcfysrCyEhIQAAOzt7fHMM8+gbdu2AIBXX31VPNfy8nKUlZXhm2++wYEDB3Dp0iXxfRkeHo6nn34aXl5ekMvlCA0NxR9//IF9+/ZhyJAhWs9r6dKlePvtt7F37148/vjjdfrsiYiIQHJyMnbu3Im9e/ciKSnpoV/QrVu3Rv/+/cW6OnXqFGQyGU6cOIGioiKxPn18fGBqaopp06Zh9erVsLGxgVKpxKFDh3Dz5k2UlJRg8uTJNY5fWVmJp556CpWVlfj6668RFxcHOzs7pKenAwB++eUXPPXUU7C0tIS1tTVCQ0Pxxhtv4PXXX8esWbPwr3/9C0eOHMHnn38OAHjllVegUCiwbNky8TVKSkrw8ccfY8OGDTh9+jQcHBxw9+5dzJgxAwcPHkRKSgq6deuGiRMn4u7du1rr4bHHHkO7du2QnJwM4H6LYvVldT2or6G6fg9UN3v2bJiYmCA4OBhbt27F+vXrkZ+fr7XspUuXsHz5cjEBeO6552BtbY3t27cDuN9iMXfuXBw+fLhOr/0wTXHu06dPx7Vr15CUlITt27frPHddnyUuLi7iuZ89exY5OTlYvXp13U5QaMZmzJghBAYG1lj/4YcfCmPHjtVYd/nyZQGAcPbsWUEQBMHHx0cYNWqURpnBgwcLb731liAIgrB7927B1NRUyMnJEbcnJCQIAIQdO3YIgiAIWVlZAgDhxIkTNeJydXUVKisrxXVTpkwRpk6d2tBTrXF8bectCIIwdepUoWfPnoIgCBqxarNs2TJh4MCB4vKiRYsEKysrobCwUFw3btw4wc3NTVCpVOK6Hj16CFFRUYIgCIJSqRRsbW2Fe/fuaRy7a9euwueffy4et1+/fhrb67qfmZmZkJ+fr/McGmLGjBmCXC4XrK2tNf5ZWFgIAITbt28LL774ovDKK6/UiNnExEQoLS0VBEEQXF1dhZUrVwqCUL/rZcOGDWKZ06dPCwCEM2fOCIIgCJs2bRJat26tNe4vvvhCsLa2FioqKoTCwkLB1NRUyM/PF7Zs2SJ4e3sLgiAI+/btEwAIFy9eFPcDILz77rviclFRkQBA2L17tyAIgrBw4UKhR48eQlVVlVjm008/FWxsbMTfu4+PjzB//nxBEATh4sWLglwuF65evaoR3+OPPy5ERkZqjf327duCiYmJ8McffwhVVVWCnZ2dEBUVJQwdOlQQBEH49ttvhY4dO4rlu3btKmzZskXjGM8884wgl8sFCwsLYeDAgQIAYdu2bYIgCMJbb70l9O7dW+Nc33nnHQGAeK6bNm0SAAitWrXSOM/WrVsL6o/KGTNmCG3bthWmTZum9TwE4X+/9wULFgjOzs5Cenq6uK22z567d+8K5ubmwg8//CBuv3nzpmBpaSnWrzahoaHCpEmTBEEQhFWrVglTp04V+vXrJ/4OPTw8hPXr1wuCIAgff/yxAEDYv3+/uP+oUaMEuVwu/Prrr4IgCEK/fv0EW1tbQRAEITs7WwAgvP/++2L5O3fuCFZWVsL8+fOF4cOHC9OmTRNcXV2Ff/7zn2KZqqoqoV27doKJiYlw9epVjc/D6teCut7T0tJ0np8gCIJKpRJatWol/PzzzzrLBAcHC7NnzxYEQRDeeOMNISIiQmjbtq1w5swZoby8XLCyshL27t0rCELdvwfU9X7mzBkBgPDxxx8Lbdu2FSwsLAQvLy8BgBARESEeQ31Nqa8z9ftJfZ0lJiYKAIQxY8bU+bUFQfPzxFDn/scff4jlz58/LwDQiKm2zxL1ud++fVvneWjTIvuonDx5EomJibCxsamxLTMzE927dweAGvdqnZ2dxQzy7NmzcHFx0ejnoeuvKm0ee+wxyOVyjWOfOnWqXufREIIgQCaTad22bds2fPLJJ8jMzERRUREqKytrPH3Tzc0NrVq1EpcdHR3F5s3q69T1dPLkSRQVFaFdu3YaxyktLX1oZ8667ufq6vpI+oL4+flh7dq1GuuOHj2Kf/7zn2J8f/75J7777jtxuyAIqKqqQlZWFnr27Kmxb32ul+rXnbOzMwAgPz8fnp6eD43Z19cXxcXF+OOPP3D79m10794d7du3h4+PD2bOnIl79+4hKSkJXbp0QefOnXW+prW1NWxtbcXf4ZkzZzB8+HCN62bkyJEoKirClStXahzr1KlTUKlU4vtIraysrMbvU61Nmzbo168fkpKSYG5uDnNzc7zyyitYtGgRioqKxBYB4P6tkczMTLz44ot4+eWXxWNUVlbCzs4O3333ndgK99xzz6GkpARnz57F4MGDkZ6eLp6ruv5btWolnqu5ubnGtezs7IyCggKNWAsLC/H444/r+jUAAKKjo1FcXIxjx46hS5cu4vraPntKS0tRXl6OoUOHiuvt7OzQo0ePh76ej48PvvzyS6hUKiQnJ2Ps2LFwcnJCUlIS+vbtiwsXLoh/TatvD4wdOxYKhQJVVVUoLS0VY3iQuuNjVFQUjh07hieeeAJPP/20GFNaWhpefvllHDx4UOM6kslkaNWqFW7evInu3btD+L9J0EeMGIGKigqNa8Hc3LzG521eXh7effddJCUlIT8/HyqVCiUlJbh06dJD62H9+vUA7rcgLFmyBOfOnUNSUhJu3bqFiooKjBw5EkDdvwfUzp49C1NTU4SHh2PevHlQKpVISUnByZMnER0djV69emncylCfj/r9VFFRgfz8fPH9olQq6/zaddEU5+7l5SWu8/DwEFslq3vYZ0lDtchEpaioCE8++SQ+/vjjGtvUXwwAYGZmprFNJpNpjJppjEd57Ic5c+aMeK+4uiNHjmDatGlYvHgxxo0bh9atW+P777+vcX9cW9wPO5eioqIafSfUHjYUtK77WVtb6zxGY1hbW8PDw0Nj3ZUrVzTie/XVVzFv3rwa+z74xV1f1etTnRzU5drw8PBAp06dkJiYiNu3b4tf7B06dICLiwsOHz6MxMREjBkz5qGvqX7dhl6PRUVFkMvlSE1N1UjGAWj9YFTz9fVFUlISFAoFfHx8YGdnh549e+LgwYNITk5GWFiYeHwA+OKLLzS+0AFALpfD3d0d3bp1w8qVK/Hkk09i0aJFGh+wDztXuVwufqGqtz2oLp08R48ejV9++QU//PAD3n77bXF9bZ89Fy5cqPXY2nh7e+Pu3bs4fvw4Dhw4gCVLlsDJyQn/+c9/0K9fP3To0AHdunUTY3B3d0dubi4OHjyI9evX45dffsFvv/0GBwcHna8RGxuLkydPYtu2bXj33XfRoUMHAIClpaVY5sG6raqqgkwmQ2pqKnJycuDn54fvv/8evXr10rgWLC0ta9T1jBkzcPPmTaxevRqurq5QKBQYPnw4ysvLdcao7ldx/vx5/PXXXxg1ahQyMjKQlJSE27dvY9CgQbCyshLroS7fA9pYWFjA398f/v7+WLlyJbp3745FixZpJCq1vY/Hjx+PFStW1Pu1dWmqc6/No/hua5GJipeXF7Zv3w43NzeYmjasCnr06IHLly8jLy8Pjo6OAO4PR61OPQJFfd/d0Pbv349Tp07hzTffrLHt8OHDcHV11eg3cfHixUa/ppeXF3Jzc2Fqago3NzetZczNzWvUUV32MyQvLy/89ddfNZIZXepyvdSFtrqqzs/PT/xgioiIENd7e3tj9+7d+P333zFr1qx6vWbPnj2xfft2jda4Q4cOoVWrVjVGjgD3O0uqVCrk5+dj9OjRdX4dHx8fbNy4EaampuIQWl9fX2zduhXnzp0TWwQcHR3RoUMH/P3335g2bdpDj9mlSxcolUr06NEDu3bt0timrf5lMhnu3r2L4uJirUmwubk5bG1tsW/fPsycOVPn6w4ZMgRz5szB+PHjxb/Cgdo/e7p27QozMzMcPXpUTHhv376Nc+fOiYmnNm3atEHfvn3x3//+F2ZmZvD09ISDgwOmTp2K+Ph4jX29vLzw/fffQy6X4+jRo/j5558xa9YsMZF5UJcuXWBmZobS0lJERkYiMjISQ4YMEYcv9+3bV+wo/CArKysIgoD8/Hzxr/SOHTvW6X1z6NAhfPbZZ5g4cSIA4PLly7V2Nu3Tpw/atm2Ljz76CP3794eNjQ18fX3x8ccf4/bt2xoDGur7PdCjRw9UVlbixIkTGDhwIID7feRu374NJyenOieZ6u+FM2fONOo76EGGOvf6aOh3YrPvTFtQUIC0tDSNf6+88gpu3bqFZ599Fn/88QcyMzPx66+/YubMmXWuQH9/f3Tt2hUzZszAn3/+iUOHDuHdd98F8L/s2cHBAZaWlmJHpQebkB+lsrIy5Obm4urVqzh+/DiWLFmCwMBABAQEYPr06TXKd+vWDZcuXcL333+PzMxMfPLJJ9ixY0ej43jiiScwfPhwBAUFYe/evcjOzsbhw4fxzjvviKMU3NzckJWVhbS0NNy4cQNlZWV12s+Q3nrrLRw+fBhz5sxBWloazp8/j507d+rsTFuX66Uu3NzcUFRUhH379uHGjRsoKSnR2O7n54eDBw8iLS1N48vJx8cHn3/+OcrLy2t0pK3N66+/jsuXL2Pu3LnIyMjAzp07sWjRIoSGhmptXejevTumTZuG6dOnIzY2FllZWfj9998RFRWFX375RefrqFsF4uPjxQ9VX19ffPfdd3B2dtZojl68eDGioqLwySef4Ny5c1AqlejZsyemTZuGP//8E5cvXwZwv0N8YGAgXn31VWRkZAAArl27hh9++EFr53W5XA4rKyssXLgQmZmZOHDggMZ2Nzc3yOVybN26FREREfjzzz9x6tQprX+ZjhgxArt27cLixYvFkRGzZ89+6GePjY0NXnzxRURERGD//v1IT0/H888/X6dWHHVdqX/v6hapbdu2aVwL06ZNQ/v27WFjY4OIiAjk5OSge/fumDdvnkarodqNGzfQq1cvzJ07V+xAevLkScjlcshkMixatAhbt27FnTt3kJeXp1EfCoUCffr0wfTp03Ho0CEoFAps2LAB77zzDn744YeHnk+3bt3wzTff4MyZMzh69CimTZum0XqjjUwmg7e3N7777jvxGurbty/Kysqwb98+jXqo7XfxIE9PT3h7e8PX1xeLFy/Gtm3b8K9//Qvm5ubYv38/AgMDHxqbmqurK4D7t7aCg4ORnJzcoO+gpj73J554Aq+88gp+//13nDhxAq+88orWlrDazl0mkyE+Ph7Xr18XW0drVa8eLUZmxowZYiem6v9efPFF4dy5c8JTTz0ltGnTRrC0tBQ8PT2FN954Q+ww+GBHJkEQhMDAQGHGjBni8pkzZ4SRI0cK5ubmgqenp/Dzzz8LAIQ9e/aIZb744gvBxcVFMDExEXx8fMS4HuzsOn/+fHG7Ps/b1NRUaN++vfDEE08IGzdu1Oj0igc600ZERAjt2rUTbGxshKlTpworV67U6LiprdOrtnN5sO4KCwuFuXPnCh06dBDMzMwEFxcXYdq0acKlS5cEQRCEe/fuCZMnTxbatGkjABA2bdpUp/20xaMPujojP9gR7Pfffxf8/f0FGxsbwdraWujbt6/w73//Wyz/YOe32q4XbZ2vb9++LQAQEhMTxXWvvfaa0K5dOwGAsGjRIo0Y1cfw9PTUWK/uENmjR48a5/XgdSAIgtC6dWvx9yAIgpCUlCQMHjxYMDc3F5ycnIS33npLqKioELc/+DsvLy8X3nvvPcHNzU0wMzMTnJ2dhaeeekr4888/a7x+df369ROcnJzE5Zs3bwoymUx45plnapT97rvvhP79+wvm5uZCmzZtBBcXF6FLly5C69atBUtLSwGA8NJLLwklJSWCIAjCzp07xfeEr6+vsHbtWgGAeK7qjso7duwQPDw8BEtLS2HQoEHie0kQBCE/P1/w9/cXO1abmZkJ9vb2QnBwsBjXg7/35ORkwdraWvjkk08EQRBq/ey5e/eu8M9//lOwsrISHB0dhaVLl2r9PHrQjh07BADC2rVrxXXz588XAAgZGRkaZXNycoQJEyYIAAQTExOhS5cuwssvvywUFBSIvwd1Z9rc3FwhICBArFMTExNh7NixwuDBg4W3335bEARB2L59u2BmZibI5XKN+ujXr5/w7rvviteCXC4XTExMBABiR31dHcSPHz8uDBo0SLCwsBC6desm/Pjjj7V2KBUEQVi5cqVGB05BuP/ZbWpqKty9e1ejbH2/B7KysoQuXboIMplMkMlkgkKhEORyuTBx4kTxOlNfL9XfU+prUv2e+uCDDwR7e3sBgGBubl6n1zb0uV+7dk2YMGGCoFAoBFdXV2HLli2Cg4ODsG7dOrFMXT5LPvjgA8HJyUmQyWQa36cPI/u/g5MeHDp0CKNGjcKFCxea3WRapH+8Xgzr3//+N9atWye2vlDdFRcXo2PHjoiOjhbnXmmJrly5AhcXF/z222+1drBubpry3FtkHxV92bFjB2xsbNCtWzdcuHAB8+fPx8iRI/mlQ1rxejGszz77DIMHD0a7du1w6NAhLFu2TOetOtJ04sQJZGRkYMiQISgoKMAHH3wAAHW+3dFc7N+/H0VFRejTpw9ycnKwYMECuLm5wdvb29ChPXKGPHcmKo1w9+5dvPXWW7h06RLs7e3xxBNP1DqLJLVcvF4M6/z58/joo49w69YtdO7cGWFhYYiMjDR0WEZj+fLlOHv2LMzNzTFw4EAolUrY29sbOqwmVVFRgYULF+Lvv/9Gq1atMGLECHz33Xc1Rro0R4Y8d976ISIiIslq9qN+iIiIyHgxUSEiIiLJYqJCREREksVEhYiIiCSLiQoRERFJFhMVIiIikiwmKkRERCRZTFSIiIhIspioEBERkWT9fwvd339NUGvtAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x1500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_reg.boxplot()\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# 종속변수 제외\n",
    "boxplot_data = data_reg.drop('Rings', axis=1)\n",
    "\n",
    "boxplot_data.boxplot()\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Sex</th>\n",
       "      <th>Length</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>Whole weight</th>\n",
       "      <th>Shucked weight</th>\n",
       "      <th>Viscera weight</th>\n",
       "      <th>Shell weight</th>\n",
       "      <th>Rings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1257</th>\n",
       "      <td>I</td>\n",
       "      <td>0.430</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.428</td>\n",
       "      <td>0.2065</td>\n",
       "      <td>0.0860</td>\n",
       "      <td>0.1150</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3996</th>\n",
       "      <td>I</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.0575</td>\n",
       "      <td>0.0285</td>\n",
       "      <td>0.3505</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Sex  Length  Diameter  Height  Whole weight  Shucked weight  \\\n",
       "1257   I   0.430      0.34     0.0         0.428          0.2065   \n",
       "3996   I   0.315      0.23     0.0         0.134          0.0575   \n",
       "\n",
       "      Viscera weight  Shell weight  Rings  \n",
       "1257          0.0860        0.1150      8  \n",
       "3996          0.0285        0.3505      6  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Height에 이상치 : 0인 것, 1.13인 것\n",
    "data_reg[data_reg['Height']==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Sex</th>\n",
       "      <th>Length</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>Whole weight</th>\n",
       "      <th>Shucked weight</th>\n",
       "      <th>Viscera weight</th>\n",
       "      <th>Shell weight</th>\n",
       "      <th>Rings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2051</th>\n",
       "      <td>F</td>\n",
       "      <td>0.455</td>\n",
       "      <td>0.355</td>\n",
       "      <td>1.13</td>\n",
       "      <td>0.594</td>\n",
       "      <td>0.332</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.1335</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Sex  Length  Diameter  Height  Whole weight  Shucked weight  \\\n",
       "2051   F   0.455     0.355    1.13         0.594           0.332   \n",
       "\n",
       "      Viscera weight  Shell weight  Rings  \n",
       "2051           0.116        0.1335      8  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Height에 이상치 : 0인 것, 1.13인 것\n",
    "data_reg[data_reg['Height']==1.13]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove rows where 'Height' is 0 or 1.13\n",
    "data_reg = data_reg[(data_reg['Height'] != 0) & (data_reg['Height'] != 1.13)]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Shucked weight의 min, max 값의 차이가 커서 로그 변환을 사용하여 데이터를 더 정규 분포에 가깝게 만들어 봄. \n",
    "\n",
    "다시 정리해보면, \n",
    "\n",
    "Scaling: 값의 범위를 줄이기 위해 스케일링을 수행 가능함. StandardScaler는 데이터를 평균이 0이고 표준 편차가 1인 분포로 변환. MinMaxScaler는 모든 특성을 0과 1 사이로 조정.  \n",
    "\n",
    "Log Transformation: 데이터가 한쪽으로 치우쳐져 있거나 특성의 값이 지수적으로 증가할 때 로그 변환을 사용하여 데이터를 더 정규 분포에 가깝게 만들 수 있음. 이는 특히 회귀 문제에서 유용.\n",
    "\n",
    "Outlier Removal: 값이 너무 높거나 너무 낮은 이상치를 제거할 수 있음. 이상치는 종종 기계 학습 모델의 성능을 저하시키기 때문."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Remove rows where 'Shucked weight' is less than or equal to 0.01\n",
    "# data_reg = data_reg[data_reg['Shucked weight'] > 0.01]  # shucked weight에서 너무 작은 값들을 조정해가며 삭제해봤으니 RMSE 점수가 삭제 안하는 것이 가장 좋음."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reset the index of the dataframe\n",
    "data_reg = data_reg.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\anaconda3\\envs\\TeamProject\\Lib\\site-packages\\sklearn\\preprocessing\\_encoders.py:972: FutureWarning: `sparse` was renamed to `sparse_output` in version 1.2 and will be removed in 1.4. `sparse_output` is ignored unless you leave `sparse` to its default value.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "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>Length</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>Whole weight</th>\n",
       "      <th>Shucked weight</th>\n",
       "      <th>Viscera weight</th>\n",
       "      <th>Shell weight</th>\n",
       "      <th>Sex_Female</th>\n",
       "      <th>Sex_Infant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>0.485</td>\n",
       "      <td>0.390</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.5910</td>\n",
       "      <td>0.2870</td>\n",
       "      <td>0.141</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>0.570</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.135</td>\n",
       "      <td>1.0200</td>\n",
       "      <td>0.5460</td>\n",
       "      <td>0.204</td>\n",
       "      <td>0.2500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2413</th>\n",
       "      <td>0.400</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.2870</td>\n",
       "      <td>0.1135</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.1130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954</th>\n",
       "      <td>0.645</td>\n",
       "      <td>0.510</td>\n",
       "      <td>0.180</td>\n",
       "      <td>1.6195</td>\n",
       "      <td>0.7815</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.4675</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945</th>\n",
       "      <td>0.635</td>\n",
       "      <td>0.525</td>\n",
       "      <td>0.160</td>\n",
       "      <td>1.1950</td>\n",
       "      <td>0.5435</td>\n",
       "      <td>0.246</td>\n",
       "      <td>0.3350</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Length  Diameter  Height  Whole weight  Shucked weight  Viscera weight  \\\n",
       "554    0.485     0.390   0.125        0.5910          0.2870           0.141   \n",
       "2661   0.570     0.450   0.135        1.0200          0.5460           0.204   \n",
       "2413   0.400     0.315   0.105        0.2870          0.1135           0.037   \n",
       "1954   0.645     0.510   0.180        1.6195          0.7815           0.322   \n",
       "1945   0.635     0.525   0.160        1.1950          0.5435           0.246   \n",
       "\n",
       "      Shell weight  Sex_Female  Sex_Infant  \n",
       "554         0.1200         1.0         0.0  \n",
       "2661        0.2500         0.0         1.0  \n",
       "2413        0.1130         0.0         1.0  \n",
       "1954        0.4675         0.0         0.0  \n",
       "1945        0.3350         0.0         1.0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Separate the features and the target\n",
    "X_reg = data_reg.drop(\"Rings\", axis=1)\n",
    "y_reg = data_reg[\"Rings\"]\n",
    "\n",
    "# Apply one-hot encoding to the 'Sex' feature\n",
    "encoder = OneHotEncoder(sparse=False, drop='first')\n",
    "sex_encoded = encoder.fit_transform(X_reg[['Sex']])\n",
    "sex_encoded_df = pd.DataFrame(sex_encoded, columns=['Sex_Female', 'Sex_Infant'], index=X_reg.index) # add index=X_reg.index\n",
    "\n",
    "\n",
    "# sex_encoded_df = pd.DataFrame(sex_encoded, columns=encoder.get_feature_names(['Sex']))\n",
    "\n",
    "# Replace the 'Sex' column with the encoded columns\n",
    "X_reg = X_reg.drop(\"Sex\", axis=1)\n",
    "X_reg = pd.concat([X_reg, sex_encoded_df], axis=1)\n",
    "\n",
    "# Split the data into training and test sets\n",
    "X_train_reg, X_test_reg, y_train_reg, y_test_reg = train_test_split(X_reg, y_reg, test_size=0.2, random_state=42)\n",
    "\n",
    "X_train_reg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1100x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Compute the correlation matrix\n",
    "corr = X_reg.corr()\n",
    "\n",
    "# Generate a mask for the upper triangle\n",
    "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
    "\n",
    "# Set up the matplotlib figure\n",
    "f, ax = plt.subplots(figsize=(11, 9))\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
    "\n",
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "# Here, we will not use the mask, and add the annotation to display the correlation scores\n",
    "sns.heatmap(corr, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5}, annot=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 회귀모델학습"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "평균 제곱 오차 (Mean Squared Error, MSE): 4.626032551091537\n",
      "평균 제곱근 오차 (Root Mean Squared Error, RMSE): 2.1508213666159115\n",
      "평균 절대 오차 (Mean Absolute Error, MAE): 1.5419952981175713\n",
      "결정 계수 (R^2 Score): 0.5963499952525424\n"
     ]
    }
   ],
   "source": [
    "# Initialize a linear regression model\n",
    "model_reg = LinearRegression()\n",
    "\n",
    "# Fit the model to the training data\n",
    "model_reg.fit(X_train_reg, y_train_reg)\n",
    "\n",
    "# Use the model to make predictions on the test data\n",
    "y_pred_reg = model_reg.predict(X_test_reg)\n",
    "\n",
    "# Calculate the performance metrics\n",
    "mse = mean_squared_error(y_test_reg, y_pred_reg)\n",
    "rmse = np.sqrt(mse)\n",
    "mae = mean_absolute_error(y_test_reg, y_pred_reg)\n",
    "r2 = r2_score(y_test_reg, y_pred_reg)\n",
    "\n",
    "print(\"평균 제곱 오차 (Mean Squared Error, MSE):\", mse)\n",
    "print(\"평균 제곱근 오차 (Root Mean Squared Error, RMSE):\", rmse)\n",
    "print(\"평균 절대 오차 (Mean Absolute Error, MAE):\", mae)\n",
    "print(\"결정 계수 (R^2 Score):\", r2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 평균 제곱 오차 (MSE)와 평균 제곱근 오차 (RMSE)는 실제 값과 예측 값의 차이를 제곱하여 평균한 값입니다. 이 값이 작을수록 모델의 성능이 좋다고 할 수 있습니다.\n",
    "\n",
    "- 평균 절대 오차 (MAE)는 실제 값과 예측 값의 차이를 절대값으로 변환하여 평균한 값입니다. 이 값도 작을수록 모델의 성능이 좋다고 할 수 있습니다.\n",
    "\n",
    "- 결정 계수 (R^2 Score)는 회귀 모델이 데이터를 얼마나 잘 설명하는지를 나타내는 지표입니다. 이 값이 1에 가까울수록 모델이 데이터를 잘 설명하고 있다고 할 수 있습니다."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 라쏘 회귀모델 학습"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "평균 제곱 오차 (Mean Squared Error, MSE): 4.6245079710392965\n",
      "평균 제곱근 오차 (Root Mean Squared Error, RMSE): 2.1508213666159115\n",
      "평균 절대 오차 (Mean Absolute Error, MAE): 1.5463270494373558\n",
      "결정 계수 (R^2 Score): 0.5964830243089807\n"
     ]
    }
   ],
   "source": [
    "# Initialize a lasso regression model\n",
    "lasso_reg = Lasso()\n",
    "\n",
    "parameters = {'alpha': [0.001, 0.01, 0.1, 1, 10, 100, 1000]}\n",
    "\n",
    "\n",
    "# Perform grid search\n",
    "grid_search = GridSearchCV(lasso_reg, parameters, cv=5)\n",
    "grid_search.fit(X_train_reg, y_train_reg)\n",
    "\n",
    "# Get the best model\n",
    "best_model = grid_search.best_estimator_\n",
    "\n",
    "# Use the model to make predictions on the test data\n",
    "y_pred_reg = best_model.predict(X_test_reg)\n",
    "\n",
    "# Calculate the performance metrics\n",
    "lasso_mse = mean_squared_error(y_test_reg, y_pred_reg)\n",
    "lasso_rmse = np.sqrt(mse)\n",
    "lasso_mae = mean_absolute_error(y_test_reg, y_pred_reg)\n",
    "lasso_r2 = r2_score(y_test_reg, y_pred_reg)\n",
    "\n",
    "print(\"평균 제곱 오차 (Mean Squared Error, MSE):\", lasso_mse)\n",
    "print(\"평균 제곱근 오차 (Root Mean Squared Error, RMSE):\", lasso_rmse)\n",
    "print(\"평균 절대 오차 (Mean Absolute Error, MAE):\", lasso_mae)\n",
    "print(\"결정 계수 (R^2 Score):\", lasso_r2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 특성 스케일링 - 표준화 후 성능 메트릭"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "평균 제곱 오차 (Mean Squared Error, MSE): 4.62457680181735\n",
      "평균 제곱근 오차 (Root Mean Squared Error, RMSE): 2.150482922930882\n",
      "평균 절대 오차 (Mean Absolute Error, MAE): 1.5421460520050585\n",
      "결정 계수 (R^2 Score): 0.5964770183970938\n"
     ]
    }
   ],
   "source": [
    "# Initialize a standard scaler\n",
    "scaler = StandardScaler()\n",
    "\n",
    "# Fit the scaler to the training data and transform the data\n",
    "X_train_scaled = scaler.fit_transform(X_train_reg)\n",
    "\n",
    "# Transform the test data\n",
    "X_test_scaled = scaler.transform(X_test_reg)\n",
    "\n",
    "# Perform grid search with the scaled data\n",
    "grid_search = GridSearchCV(lasso_reg, parameters, cv=5)\n",
    "grid_search.fit(X_train_scaled, y_train_reg)\n",
    "\n",
    "# Get the best model\n",
    "best_model = grid_search.best_estimator_\n",
    "\n",
    "# Use the model to make predictions on the test data\n",
    "y_pred_reg = best_model.predict(X_test_scaled)\n",
    "\n",
    "# Calculate the performance metrics\n",
    "mse = mean_squared_error(y_test_reg, y_pred_reg)\n",
    "rmse = np.sqrt(mse)\n",
    "mae = mean_absolute_error(y_test_reg, y_pred_reg)\n",
    "r2 = r2_score(y_test_reg, y_pred_reg)\n",
    "\n",
    "print(\"평균 제곱 오차 (Mean Squared Error, MSE):\", mse)\n",
    "print(\"평균 제곱근 오차 (Root Mean Squared Error, RMSE):\", rmse)\n",
    "print(\"평균 절대 오차 (Mean Absolute Error, MAE):\", mae)\n",
    "print(\"결정 계수 (R^2 Score):\", r2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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