Elo - ML model - cat aggregates.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Load-imports-and-dfs\" data-toc-modified-id=\"Load-imports-and-dfs-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Load imports and dfs</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.notebook.set_autosave_interval(120000)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Autosaving every 120 seconds\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 4\n",
    "%autosave 120"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Load imports & test, train DFs\n",
    "2. Apply stratified kfold & traing with lgbm and submit to kaggle\n",
    "3. Check for missing data feature engineering parts missed if score > 3.7\n",
    "4. Split the training set to train & validation\n",
    "5. Train over RF to get a benchmark of the dataset\n",
    "6. Drop irrelevant features by sorting on feature importance\n",
    "7. Drop redundant features by plotting a Dendogram and removing the redundancy\n",
    "8. Use a feature interpreter to see which feature is contributing lot to prediction\n",
    "9. Use extrapolation to see if we can remove feature which add bias of training & validation set\n",
    "10. Use partial dependence plot to see outliers/missed features\n",
    "11. Submit to kaggle the RF model and see the score\n",
    "11. Use stratified kfold to train the RF model and submit to kaggle\n",
    "12. Repeat again with LGBM/XGBoost/Adaboost. Stack the model and submit to kaggle\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load imports and dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.io import *\n",
    "from fastai.structured import *\n",
    "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
    "from pandas_summary import DataFrameSummary\n",
    "from IPython.display import display\n",
    "from sklearn import metrics\n",
    "import feather\n",
    "import lightgbm as lgb\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df2 = feather.read_dataframe('train_df')\n",
    "test_df2 = feather.read_dataframe('test_df')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "for df in [train_df2, test_df2]:\n",
    "    for f in ['purchase_date_max','purchase_date_min','purchase_date_max_old',\\\n",
    "                     'purchase_date_min_old']:\n",
    "        df[f] = df[f].astype(np.int64) * 1e-9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "del_cols = ['first_active_monthIs_month_start', 'authorized_flag_1_mean', 'first_active_monthIs_year_start',\n",
    "       'first_active_monthIs_year_end', 'first_active_monthIs_quarter_end', 'avg_trans_per_merchant',\n",
    "       'first_active_monthIs_month_end', 'first_active_monthDay', 'card_id_size',\n",
    "       'authorized_flag_1_amount_mean_mean', 'authorized_flag_1_amount_sum_sum','card_id', 'first_active_month','target','outliers']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def one_hot_encode_fe(df):\n",
    "    return pd.get_dummies(df, columns=['feature_1', 'feature_2', 'feature_3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# [train_df2, test_df2] = [one_hot_encode_fe(d) for d in [train_df2, test_df2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_columns = [c for c in train_df2.columns if c not in ['card_id', 'first_active_month','target','outliers']]\n",
    "target = train_df2['target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((201917, 116), (123623, 114))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df2.shape, test_df2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(201917,)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "del train_df2['target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "112"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_train_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 112/112 [00:02<00:00, 37.73it/s]\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import ks_2samp\n",
    "list_p_value =[]\n",
    "\n",
    "for i in tqdm(df_train_columns):\n",
    "    list_p_value.append(ks_2samp(test_df2[i] , train_df2[i])[1])\n",
    "\n",
    "Se = pd.Series(list_p_value, index = df_train_columns).sort_values() \n",
    "list_discarded = list(Se[Se < .1].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['avg_spend_per_transaction',\n",
       " 'purchase_amount_mean',\n",
       " 'avg_spend_per_merchant',\n",
       " 'purchase_amount_max_old',\n",
       " 'category_3_amount_mean_mean_old',\n",
       " 'purchase_amount_sum']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_discarded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_columns = [c for c in df_train_columns if c not in list_discarded]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "116"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_train_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# train_df2.fillna(0, inplace=True)\n",
    "# test_df2.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold 0\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.67049\tvalid_1's rmse: 3.7261\n",
      "[200]\ttraining's rmse: 3.59426\tvalid_1's rmse: 3.69365\n",
      "[300]\ttraining's rmse: 3.54711\tvalid_1's rmse: 3.67976\n",
      "[400]\ttraining's rmse: 3.51154\tvalid_1's rmse: 3.67307\n",
      "[500]\ttraining's rmse: 3.48146\tvalid_1's rmse: 3.66758\n",
      "[600]\ttraining's rmse: 3.45611\tvalid_1's rmse: 3.66441\n",
      "[700]\ttraining's rmse: 3.43308\tvalid_1's rmse: 3.66218\n",
      "[800]\ttraining's rmse: 3.41305\tvalid_1's rmse: 3.66122\n",
      "[900]\ttraining's rmse: 3.39543\tvalid_1's rmse: 3.65974\n",
      "[1000]\ttraining's rmse: 3.37818\tvalid_1's rmse: 3.65959\n",
      "[1100]\ttraining's rmse: 3.36269\tvalid_1's rmse: 3.65869\n",
      "[1200]\ttraining's rmse: 3.34563\tvalid_1's rmse: 3.65902\n",
      "Early stopping, best iteration is:\n",
      "[1100]\ttraining's rmse: 3.36269\tvalid_1's rmse: 3.65869\n",
      "fold 1\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.67157\tvalid_1's rmse: 3.71674\n",
      "[200]\ttraining's rmse: 3.59538\tvalid_1's rmse: 3.68605\n",
      "[300]\ttraining's rmse: 3.54599\tvalid_1's rmse: 3.67496\n",
      "[400]\ttraining's rmse: 3.50969\tvalid_1's rmse: 3.66911\n",
      "[500]\ttraining's rmse: 3.47927\tvalid_1's rmse: 3.66481\n",
      "[600]\ttraining's rmse: 3.45462\tvalid_1's rmse: 3.66268\n",
      "[700]\ttraining's rmse: 3.43293\tvalid_1's rmse: 3.66083\n",
      "[800]\ttraining's rmse: 3.41228\tvalid_1's rmse: 3.66043\n",
      "[900]\ttraining's rmse: 3.39362\tvalid_1's rmse: 3.65996\n",
      "[1000]\ttraining's rmse: 3.37639\tvalid_1's rmse: 3.66\n",
      "Early stopping, best iteration is:\n",
      "[934]\ttraining's rmse: 3.38738\tvalid_1's rmse: 3.65979\n",
      "fold 2\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66845\tvalid_1's rmse: 3.72706\n",
      "[200]\ttraining's rmse: 3.59031\tvalid_1's rmse: 3.69613\n",
      "[300]\ttraining's rmse: 3.54135\tvalid_1's rmse: 3.68384\n",
      "[400]\ttraining's rmse: 3.5063\tvalid_1's rmse: 3.67614\n",
      "[500]\ttraining's rmse: 3.47629\tvalid_1's rmse: 3.67106\n",
      "[600]\ttraining's rmse: 3.4512\tvalid_1's rmse: 3.66771\n",
      "[700]\ttraining's rmse: 3.42917\tvalid_1's rmse: 3.66544\n",
      "[800]\ttraining's rmse: 3.40946\tvalid_1's rmse: 3.6641\n",
      "[900]\ttraining's rmse: 3.39074\tvalid_1's rmse: 3.66292\n",
      "[1000]\ttraining's rmse: 3.37355\tvalid_1's rmse: 3.66252\n",
      "[1100]\ttraining's rmse: 3.35683\tvalid_1's rmse: 3.6621\n",
      "[1200]\ttraining's rmse: 3.34019\tvalid_1's rmse: 3.66152\n",
      "Early stopping, best iteration is:\n",
      "[1189]\ttraining's rmse: 3.3418\tvalid_1's rmse: 3.66138\n",
      "fold 3\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66744\tvalid_1's rmse: 3.72726\n",
      "[200]\ttraining's rmse: 3.58972\tvalid_1's rmse: 3.70026\n",
      "[300]\ttraining's rmse: 3.54045\tvalid_1's rmse: 3.68803\n",
      "[400]\ttraining's rmse: 3.50533\tvalid_1's rmse: 3.68012\n",
      "[500]\ttraining's rmse: 3.47559\tvalid_1's rmse: 3.67499\n",
      "[600]\ttraining's rmse: 3.45122\tvalid_1's rmse: 3.67193\n",
      "[700]\ttraining's rmse: 3.42947\tvalid_1's rmse: 3.67079\n",
      "[800]\ttraining's rmse: 3.40932\tvalid_1's rmse: 3.66861\n",
      "[900]\ttraining's rmse: 3.39048\tvalid_1's rmse: 3.66764\n",
      "[1000]\ttraining's rmse: 3.37376\tvalid_1's rmse: 3.66725\n",
      "[1100]\ttraining's rmse: 3.35646\tvalid_1's rmse: 3.66628\n",
      "[1200]\ttraining's rmse: 3.34052\tvalid_1's rmse: 3.6656\n",
      "[1300]\ttraining's rmse: 3.32484\tvalid_1's rmse: 3.66491\n",
      "[1400]\ttraining's rmse: 3.30956\tvalid_1's rmse: 3.66429\n",
      "[1500]\ttraining's rmse: 3.29447\tvalid_1's rmse: 3.6642\n",
      "Early stopping, best iteration is:\n",
      "[1484]\ttraining's rmse: 3.29706\tvalid_1's rmse: 3.66413\n",
      "fold 4\n",
      "Training until validation scores don't improve for 100 rounds.\n",
      "[100]\ttraining's rmse: 3.66955\tvalid_1's rmse: 3.712\n",
      "[200]\ttraining's rmse: 3.59012\tvalid_1's rmse: 3.68472\n",
      "[300]\ttraining's rmse: 3.54039\tvalid_1's rmse: 3.67596\n",
      "[400]\ttraining's rmse: 3.50254\tvalid_1's rmse: 3.67027\n",
      "[500]\ttraining's rmse: 3.47303\tvalid_1's rmse: 3.66705\n",
      "[600]\ttraining's rmse: 3.44737\tvalid_1's rmse: 3.66545\n",
      "[700]\ttraining's rmse: 3.42556\tvalid_1's rmse: 3.66395\n",
      "[800]\ttraining's rmse: 3.40493\tvalid_1's rmse: 3.66299\n",
      "[900]\ttraining's rmse: 3.38623\tvalid_1's rmse: 3.66279\n",
      "Early stopping, best iteration is:\n",
      "[837]\ttraining's rmse: 3.39771\tvalid_1's rmse: 3.66257\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "3.6613110690115453"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "param = {'num_leaves': 31,\n",
    "         'min_data_in_leaf': 30, \n",
    "         'objective':'regression',\n",
    "         'max_depth': -1,\n",
    "         'learning_rate': 0.01,\n",
    "         \"min_child_samples\": 20,\n",
    "         \"boosting\": \"gbdt\",\n",
    "         \"feature_fraction\": 0.9,\n",
    "         \"bagging_freq\": 1,\n",
    "         \"bagging_fraction\": 0.9 ,\n",
    "         \"bagging_seed\": 11,\n",
    "         \"metric\": 'rmse',\n",
    "         \"lambda_l1\": 0.1,\n",
    "         \"verbosity\": -1,\n",
    "         \"nthread\": 4,\n",
    "         \"random_state\": 4590}\n",
    "folds = StratifiedKFold(n_splits=5, shuffle=True, random_state=4590)\n",
    "oof = np.zeros(len(train_df2))\n",
    "predictions = np.zeros(len(test_df2))\n",
    "feature_importance_df = pd.DataFrame()\n",
    "\n",
    "for fold_, (trn_idx, val_idx) in enumerate(folds.split(train_df2,train_df2['outliers'].values)):\n",
    "    print(\"fold {}\".format(fold_))\n",
    "    trn_data = lgb.Dataset(train_df2.iloc[trn_idx][df_train_columns], label=target.iloc[trn_idx])#, categorical_feature=categorical_feats)\n",
    "    val_data = lgb.Dataset(train_df2.iloc[val_idx][df_train_columns], label=target.iloc[val_idx])#, categorical_feature=categorical_feats)\n",
    "\n",
    "    num_round = 10000\n",
    "    clf = lgb.train(param, trn_data, num_round, valid_sets = [trn_data, val_data], verbose_eval=100, early_stopping_rounds = 100)\n",
    "    oof[val_idx] = clf.predict(train_df2.iloc[val_idx][df_train_columns], num_iteration=clf.best_iteration)\n",
    "    \n",
    "    fold_importance_df = pd.DataFrame()\n",
    "    fold_importance_df[\"Feature\"] = df_train_columns\n",
    "    fold_importance_df[\"importance\"] = clf.feature_importance()\n",
    "    fold_importance_df[\"fold\"] = fold_ + 1\n",
    "    feature_importance_df = pd.concat([feature_importance_df, fold_importance_df], axis=0)\n",
    "    \n",
    "    predictions += clf.predict(test_df2[df_train_columns], num_iteration=clf.best_iteration) / folds.n_splits\n",
    "\n",
    "np.sqrt(mean_squared_error(oof, target))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Score for submission-2019-01-11 10:18:09.909061.csv - 3.6597596743401666, LB - 3.707 (included cat_1)\n",
    "2. Score for submission-2019-01-12 13:53:27.215115.csv - 3.656726211308068, LB - 3.696 (jst refactored)\n",
    "3. No changes what so ever - 3.6627995460091523\n",
    "4. Replaced with kernels code - 3.6623128394907103\n",
    "5. Replaced with kernels code along with cat_2 mean - 3.6609564684554594\n",
    "6. Added extra feature - 3.6559302073797637, LB - 3.696 (No grouping by auth flag and all)\n",
    "7. Added aggs on cat_1, auth - 3.6554801486969906, LB- 3.696\n",
    "8. Removed unnecessary cols - 3.6556548946965446, LB - 3.696\n",
    "9. Removed aggs on cat_1 - 3.654208034404632, LB - 3.697\n",
    "10. Removed unnecessary del_cols - 3.65493381575084, LB - 3.697\n",
    "11. One hot encoded features - 3.6558286566186897\n",
    "12. Added monthly aggregates - 3.653533666238162, LB - 3.716\n",
    "13. Removed some monthly aggregates - 3.654769374794982, LB - 3.707\n",
    "14. reverting to earlier checkpoing - 3.65377489489624\n",
    "15. Benchmarks - LGBM - 3.654910478618945, DL - 3.6971527526968155\n",
    "16. Aggregated on cat_1, cat_2, cat_3 - 3.6613473953411266, LB - 3.734\n",
    "17. Aggregated on authorized trans - 3.660471359804697, LB - \n",
    "18. Removed filling of NaNs with 0s in cat aggregates - 3.6613219418574943, \n",
    "19. Filling NaNs with 0s for all df values - 3.662186022939442\n",
    "20. Removed cat aggs - agg only on authorized - 3.6612178198254326"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/chandrasekhar/anaconda3/envs/fastai/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = (feature_importance_df[[\"Feature\", \"importance\"]]\n",
    "        .groupby(\"Feature\")\n",
    "        .mean()\n",
    "        .sort_values(by=\"importance\", ascending=False)[:1000].index)\n",
    "\n",
    "best_features = feature_importance_df.loc[feature_importance_df.Feature.isin(cols)]\n",
    "\n",
    "plt.figure(figsize=(14,25))\n",
    "sns.barplot(x=\"importance\",\n",
    "            y=\"Feature\",\n",
    "            data=best_features.sort_values(by=\"importance\",\n",
    "                                           ascending=False))\n",
    "plt.title('LightGBM Features (avg over folds)')\n",
    "plt.tight_layout()\n",
    "plt.savefig('lgbm_importances.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['first_active_monthIs_month_end', 'first_active_monthIs_month_start',\n",
       "       'first_active_monthIs_quarter_end', 'card_id_size', 'first_active_monthIs_year_end',\n",
       "       'first_active_monthIs_year_start', 'authorized_flag_mean', 'first_active_monthDay',\n",
       "       'avg_trans_per_merchant', 'repurchase_merchant_rate', 'authorized_flag_sum'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_features.sort_values(by='importance', ascending=True)[:50]['Feature'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub_df = pd.DataFrame({\"card_id\":test_df2[\"card_id\"].values})\n",
    "sub_df[\"target\"] = predictions\n",
    "sub_df.to_csv(f'submission-{pd.to_datetime(\"today\")}.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'Elo - ML model - cat aggregates.ipynb'\r\n",
      "'Elo - ML model clean.ipynb'\r\n",
      "'Elo - ML model proc_df.ipynb'\r\n",
      "'Elo - ML model-RF copy.ipynb'\r\n",
      "'Elo - ML model-backup.ipynb'\r\n",
      "'Elo - ML model-new.ipynb'\r\n",
      "'Elo - ML model.ipynb'\r\n",
      "'Elo RF- New.ipynb'\r\n",
      "'Elo RF.ipynb'\r\n",
      "'Elo end 2 end.ipynb'\r\n",
      "'Elo feature engineering using agg.ipynb'\r\n",
      "'Elo feature engineering-backup.ipynb'\r\n",
      "'Elo feature engineering-proc_df - new-Copy1.ipynb'\r\n",
      "'Elo feature engineering-proc_df - new.ipynb'\r\n",
      "'Elo feature engineering-proc_df-OLD.ipynb'\r\n",
      "'Elo feature engineering.ipynb'\r\n",
      "'Elo merchant category reco - using RF.ipynb'\r\n",
      " README.md\r\n",
      "'Scrap pad.ipynb'\r\n",
      "'Scrap pad.py'\r\n",
      "'TS Fresh.ipynb'\r\n",
      "'TS Fresh.py'\r\n",
      "'Train & test clean.ipynb'\r\n",
      "'Using DL.ipynb'\r\n",
      "'Using Feature tools.ipynb'\r\n",
      " adf\r\n",
      " authorised_trans_proc_agg\r\n",
      " cols_keep.npy\r\n",
      " data\r\n",
      " df_auth\r\n",
      " df_hot_dropped_all\r\n",
      " df_hot_ext\r\n",
      " df_hot_test\r\n",
      " df_hot_test_ext\r\n",
      " df_new\r\n",
      " df_non_auth\r\n",
      " df_proc_dfed\r\n",
      " df_test_n_o\r\n",
      " df_xo\r\n",
      " fastai\r\n",
      " fm_new_hist\r\n",
      " hist_trans\r\n",
      " hist_trans_agg\r\n",
      " hist_trans_agg_n\r\n",
      " hist_trans_agg_proc\r\n",
      " lgbm_importances.png\r\n",
      " new_hist_prc\r\n",
      " new_hist_trans\r\n",
      " new_hist_trans_agg\r\n",
      " new_hist_trans_agg_n\r\n",
      " new_trans_agg_proc\r\n",
      " new_trans_proc_agg\r\n",
      " non_authorised_trans_proc\r\n",
      " non_authorised_trans_proc_agg\r\n",
      "'scrap pad 2.ipynb'\r\n",
      "'submission-2019-01-11 09:49:53.716164.csv'\r\n",
      "'submission-2019-01-11 10:18:09.909061.csv'\r\n",
      "'submission-2019-01-12 13:53:27.215115.csv'\r\n",
      "'submission-2019-01-12 16:27:31.239044.csv'\r\n",
      "'submission-2019-01-12 17:25:56.678553.csv'\r\n",
      "'submission-2019-01-12 17:33:29.475835.csv'\r\n",
      "'submission-2019-01-12 17:42:01.350278.csv'\r\n",
      "'submission-2019-01-12 22:12:59.947458.csv'\r\n",
      "'submission-2019-01-13 15:59:45.792347.csv'\r\n",
      "'submission-2019-01-13 18:24:51.237991.csv'\r\n",
      "'submission-2019-01-14 19:04:33.028609.csv'\r\n",
      "'submission-2019-01-14 19:56:09.906235.csv'\r\n",
      "'submission-2019-01-15 22:18:34.294443.csv'\r\n",
      "'submission-2019-01-15 22:24:38.071972.csv'\r\n",
      "'submission-2019-01-15 22:29:20.144417.csv'\r\n",
      "'submission-2019-01-16 00:35:46.490517.csv'\r\n",
      "'submission-2019-01-16 00:36:26.004443.csv'\r\n",
      "'submission-2019-01-16 12:20:00.957329.csv'\r\n",
      "'submission-2019-01-16 21:37:16.421927.csv'\r\n",
      "'submission-2019-01-17 10:20:06.724992.csv'\r\n",
      "'submission-2019-01-17 11:09:17.495216.csv'\r\n",
      "'submission-2019-01-17 23:23:57.743505.csv'\r\n",
      "'submission-2019-01-18 01:18:08.182115.csv'\r\n",
      "'submission-2019-01-18 01:42:20.587834.csv'\r\n",
      "'submission-2019-01-18 01:47:04.024727.csv'\r\n",
      "'submission-2019-01-18 16:16:45.475456.csv'\r\n",
      "'submission-2019-01-18 16:27:58.560480.csv'\r\n",
      "'submission-2019-01-18 17:22:46.188675.csv'\r\n",
      "'submission-2019-01-20 00:30:10.643280.csv'\r\n",
      "'submission-2019-01-20 01:28:12.077657.csv'\r\n",
      " target_all\r\n",
      " target_outliers_removed\r\n",
      " test_clean.csv\r\n",
      " test_clean.csv.zip\r\n",
      " test_df\r\n",
      " test_df_proc\r\n",
      " test_df_proc_new\r\n",
      " test_df_proc_new_m\r\n",
      " train_clean.csv\r\n",
      " train_clean.csv.zip\r\n",
      " train_clean0\r\n",
      " train_df\r\n",
      " train_df_proc\r\n",
      " train_df_proc_new\r\n",
      " train_df_proc_new_m\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<a href='./submission-2019-01-20 00:30:10.643280.csv' target='_blank'>./submission-2019-01-20 00:30:10.643280.csv</a><br>"
      ],
      "text/plain": [
       "/home/chandrasekhar/private/kaggle/submission-2019-01-20 00:30:10.643280.csv"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FileLink('./submission-2019-01-20 00:30:10.643280.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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