NB_rf_hyperparameters_tuning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5cbf5876",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Column:  x1 NAs:  0\n",
      "Column:  x2 NAs:  0\n",
      "Column:  x3 NAs:  4\n",
      "Column:  x4 NAs:  8\n",
      "Column:  x5 NAs:  4\n",
      "Column:  x6 NAs:  8\n",
      "Column:  x7 NAs:  3\n",
      "Column:  x8 NAs:  2\n",
      "Column:  x9 NAs:  92\n",
      "Column:  x10 NAs:  104\n",
      "Column:  x11 NAs:  1\n",
      "Column:  x12 NAs:  3\n",
      "Column:  x13 NAs:  2163\n",
      "Column:  x14 NAs:  2151\n",
      "Column:  x15 NAs:  1056\n",
      "Column:  x16 NAs:  1066\n",
      "Column:  x17 NAs:  1633\n",
      "Column:  x18 NAs:  1643\n",
      "Column:  x19 NAs:  1\n",
      "Column:  x20 NAs:  0\n",
      "Column:  x21 NAs:  390\n",
      "Column:  x22 NAs:  378\n",
      "Column:  x23 NAs:  422\n",
      "Column:  x24 NAs:  413\n",
      "Column:  x25 NAs:  0\n",
      "Column:  x26 NAs:  0\n",
      "Column:  x27 NAs:  0\n",
      "Column:  x28 NAs:  0\n",
      "Column:  x29 NAs:  0\n",
      "Column:  x30 NAs:  0\n",
      "Column:  x31 NAs:  0\n",
      "Column:  x32 NAs:  0\n",
      "Column:  x33 NAs:  0\n",
      "Column:  x34 NAs:  0\n",
      "Column:  x35 NAs:  0\n",
      "Column:  x36 NAs:  0\n",
      "Column:  x37 NAs:  25\n",
      "Column:  x38 NAs:  0\n",
      "Column:  x39 NAs:  0\n",
      "Column:  x40 NAs:  0\n",
      "Column:  c1 NAs:  0\n",
      "Column:  c2 NAs:  0\n",
      "Column:  c3 NAs:  0\n",
      "Column:  c4 NAs:  0\n",
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      "Column:  c6 NAs:  0\n",
      "Column:  c7 NAs:  0\n",
      "Column:  c8 NAs:  0\n",
      "Column:  c9 NAs:  0\n",
      "Column:  c10 NAs:  0\n",
      "Column:  c11 NAs:  0\n",
      "Column:  c12 NAs:  0\n",
      "Column:  o1 NAs:  0\n",
      "Column:  o2 NAs:  0\n",
      "Column:  y NAs:  0\n",
      "-----------------------------------\n",
      "0    3753\n",
      "1    2079\n",
      "Name: y, dtype: int64\n",
      "Percentage of minority class:  0.35648148148148145\n",
      "Column  x1 NAs:  0\n",
      "Column  x2 NAs:  0\n",
      "Column  x3 NAs:  0\n",
      "Column  x4 NAs:  0\n",
      "Column  x5 NAs:  0\n",
      "Column  x6 NAs:  0\n",
      "Column  x7 NAs:  0\n",
      "Column  x8 NAs:  0\n",
      "Column  x9 NAs:  0\n",
      "Column  x10 NAs:  0\n",
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      "Column  x12 NAs:  0\n",
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      "Column  x18 NAs:  0\n",
      "Column  x19 NAs:  0\n",
      "Column  x20 NAs:  0\n",
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      "Column  x40 NAs:  0\n",
      "Column  c1 NAs:  0\n",
      "Column  c2 NAs:  0\n",
      "Column  c3 NAs:  0\n",
      "Column  c4 NAs:  0\n",
      "Column  c5 NAs:  0\n",
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      "Column  c10 NAs:  0\n",
      "Column  c11 NAs:  0\n",
      "Column  c12 NAs:  0\n",
      "Column  o1 NAs:  0\n",
      "Column  o2 NAs:  0\n",
      "Column  y NAs:  0\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.inspection import permutation_importance\n",
    "import time \n",
    "\n",
    "from Script import *\n",
    "\n",
    "df_train = pd.read_csv(\"Data/train.csv\")\n",
    "df_test  = pd.read_csv(\"Data/test.csv\")\n",
    "\n",
    "df_train = df_train.drop(\"i\", axis=1)\n",
    "y = df_train.pop(\"y\")\n",
    "df_train.insert(54,\"y\", y)\n",
    "df_test = df_test.drop([\"y\", \"i\"], axis = 1)\n",
    "\n",
    "#Changing variable data types\n",
    "df_test.loc[:, \"c1\":\"c12\"] = df_test.loc[:, \"c1\":\"c12\"].astype(\"category\")\n",
    "df_test.loc[:, [\"o1\", \"o2\"]] = df_test.loc[:, [\"o1\", \"o2\"]].astype(\"category\")\n",
    "df_train.loc[:, \"c1\":\"c12\"] = df_train.loc[:, \"c1\":\"c12\"].astype(\"category\")\n",
    "df_train.loc[:, [\"o1\", \"o2\", \"y\"]] = df_train.loc[:, [\"o1\", \"o2\", \"y\"]].astype(\"category\")\n",
    "\n",
    "#Call relevant methods until we have results\n",
    "analyze_dataset(df_train, df_test)\n",
    "df_train, df_test = preprocess_data(df_train, df_test)\n",
    "\n",
    "\n",
    "\n",
    "X = df_train.iloc[:, 0:-1]\n",
    "y = df_train.iloc[:, -1]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7526eff7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters used:\n",
      "\n",
      "{'bootstrap': True,\n",
      " 'ccp_alpha': 0.0,\n",
      " 'class_weight': None,\n",
      " 'criterion': 'gini',\n",
      " 'max_depth': None,\n",
      " 'max_features': 'auto',\n",
      " 'max_leaf_nodes': None,\n",
      " 'max_samples': None,\n",
      " 'min_impurity_decrease': 0.0,\n",
      " 'min_samples_leaf': 1,\n",
      " 'min_samples_split': 2,\n",
      " 'min_weight_fraction_leaf': 0.0,\n",
      " 'n_estimators': 100,\n",
      " 'n_jobs': None,\n",
      " 'oob_score': False,\n",
      " 'random_state': 1,\n",
      " 'verbose': 0,\n",
      " 'warm_start': False}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "rf = RandomForestClassifier(random_state = 1)\n",
    "\n",
    "from pprint import pprint\n",
    "\n",
    "print('Parameters used:\\n')\n",
    "pprint(rf.get_params())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7117bc10",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'bootstrap': [True, False],\n",
      " 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, None],\n",
      " 'max_features': ['auto', 'sqrt'],\n",
      " 'min_samples_leaf': [1, 2, 4],\n",
      " 'min_samples_split': [2, 5, 10],\n",
      " 'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000]}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "\n",
    "n_estimators = [int(x) for x in np.linspace(200, 2000, 10)]\n",
    "max_features = ['auto', 'sqrt']\n",
    "max_depth = [int(x) for x in np.linspace(10, 110, 11)]\n",
    "max_depth.append(None)\n",
    "min_samples_split = [2, 5, 10]\n",
    "min_samples_leaf = [1, 2, 4]\n",
    "bootstrap = [True, False]\n",
    "\n",
    "random_grid = {'n_estimators' : n_estimators,\n",
    "              'max_features' : max_features,\n",
    "              'max_depth' :  max_depth,\n",
    "              'min_samples_split': min_samples_split,\n",
    "              'min_samples_leaf' : min_samples_leaf,\n",
    "              'bootstrap' : bootstrap}\n",
    "\n",
    "pprint(random_grid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2a977d6c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 100 candidates, totalling 500 fits\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomizedSearchCV(cv=5, estimator=RandomForestClassifier(), n_iter=100,\n",
       "                   n_jobs=-1,\n",
       "                   param_distributions={'bootstrap': [True, False],\n",
       "                                        'max_depth': [10, 20, 30, 40, 50, 60,\n",
       "                                                      70, 80, 90, 100, 110,\n",
       "                                                      None],\n",
       "                                        'max_features': ['auto', 'sqrt'],\n",
       "                                        'min_samples_leaf': [1, 2, 4],\n",
       "                                        'min_samples_split': [2, 5, 10],\n",
       "                                        'n_estimators': [200, 400, 600, 800,\n",
       "                                                         1000, 1200, 1400, 1600,\n",
       "                                                         1800, 2000]},\n",
       "                   random_state=1, verbose=2)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf = RandomForestClassifier()\n",
    "rf_random = RandomizedSearchCV(estimator=rf,\n",
    "                               param_distributions=random_grid,\n",
    "                               n_iter=100,\n",
    "                               cv = 5,\n",
    "                               verbose=2,\n",
    "                               random_state=1,\n",
    "                               n_jobs=-1\n",
    "                              )\n",
    "\n",
    "rf_random.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c52561b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'n_estimators': 1600,\n",
       " 'min_samples_split': 2,\n",
       " 'min_samples_leaf': 4,\n",
       " 'max_features': 'sqrt',\n",
       " 'max_depth': 70,\n",
       " 'bootstrap': True}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_random.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b731070b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Temp/rf_random_search.joblib']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import joblib\n",
    "joblib.dump(rf_random,\"Temp/rf_random_search.joblib\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "651beef0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def evaluate(model, test_features, test_labels):\n",
    "    predictions = model.predict(test_features)\n",
    "    errors = abs(predictions - test_labels)\n",
    "    mape = 100 * np.mean(errors / test_labels)\n",
    "    accuracy = 100 - mape\n",
    "    print('Model Performance')\n",
    "    print('Average Error: {:0.4f} degrees.'.format(np.mean(errors)))\n",
    "    print('Accuracy = {:0.2f}%.'.format(accuracy))\n",
    "    \n",
    "    return accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "091b1ee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "base acc 0.6812339331619537\n",
      "random acc 0.9477292202227935\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, stratify=y, random_state=1)\n",
    "\n",
    "base_model = RandomForestClassifier(random_state = 1)\n",
    "base_model.fit(X_train, y_train)\n",
    "base_acc = np.sum(y_test == base_model.predict(X_test))/len(y_test)\n",
    "print(\"base acc\", base_acc)\n",
    "\n",
    "best_random = rf_random.best_estimator_\n",
    "random_acc = np.sum(y_test == (best_random.predict(X_test)))/len(y_test)\n",
    "\n",
    "print(\"random acc\", random_acc)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "f6e6d592",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "param_grid = {\n",
    "    'bootstrap': [True],\n",
    "    'max_depth': [60, 70, 80, 90],\n",
    "    'max_features': ['sqrt'],\n",
    "    'min_samples_leaf': [3, 4, 5],\n",
    "    'min_samples_split': [2, 4, 6],\n",
    "    'n_estimators': [1400, 1600, 1800, 1900]\n",
    "}\n",
    "\n",
    "\n",
    "rf = RandomForestClassifier()\n",
    "\n",
    "\n",
    "grid_search = GridSearchCV(estimator = rf, param_grid = param_grid, \n",
    "                          cv = 5, n_jobs = -1, verbose = 3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "3160d4c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 144 candidates, totalling 720 fits\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.682 total time=  33.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.675 total time=  26.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.682 total time=  31.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.681 total time=  29.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.682 total time=  33.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.686 total time=  25.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.679 total time=  33.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.696 total time=  28.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.676 total time=  34.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.668 total time=  29.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.687 total time=  24.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.684 total time=  32.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.684 total time=  25.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.686 total time=  33.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  28.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.679 total time=  27.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.684 total time=  34.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.677 total time=  27.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.661 total time=  35.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.684 total time=  31.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.678 total time=  37.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.692 total time=  35.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.672 total time=  26.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.686 total time=  36.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.679 total time=  30.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.696 total time=  24.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.696 total time=  31.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.679 total time=  24.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  32.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.684 total time=  27.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.678 total time=  33.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.698 total time=  33.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.673 total time=  26.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.674 total time=  34.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.675 total time=  27.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.683 total time=  36.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.680 total time=  29.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.694 total time=  25.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.675 total time=  29.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.686 total time=  25.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.674 total time=  32.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.684 total time=  25.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.686 total time=  33.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.681 total time=  28.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.688 total time=  25.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.684 total time=  28.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.686 total time=  26.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.687 total time=  34.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.679 total time=  26.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.675 total time=  35.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.675 total time=  30.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.670 total time=  36.9s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.676 total time=  33.3s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.681 total time=  30.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.695 total time=  26.9s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.672 total time=  27.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.686 total time=  40.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  37.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.675 total time=  25.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.674 total time=  33.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.684 total time=  29.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.679 total time=  35.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  32.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.683 total time=  25.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.684 total time=  33.9s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.681 total time=  28.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.682 total time=  24.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.685 total time=  32.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.681 total time=  27.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.682 total time=  35.6s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.679 total time=  30.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.671 total time=  37.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.681 total time=  34.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.678 total time=  26.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.689 total time=  35.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.679 total time=  30.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.692 total time=  26.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.672 total time=  30.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.686 total time=  25.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.680 total time=  31.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.680 total time=  25.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.686 total time=  33.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.676 total time=  28.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.681 total time=  26.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.673 total time=  31.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.686 total time=  26.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.674 total time=  33.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.678 total time=  26.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.668 total time=  35.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.684 total time=  29.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.677 total time=  35.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  32.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.682 total time=  26.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.688 total time=  34.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.677 total time=  28.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.687 total time=  24.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.686 total time=  32.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.674 total time=  24.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.679 total time=  32.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.686 total time=  30.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  36.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.675 total time=  34.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.672 total time=  27.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  35.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.680 total time=  29.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.685 total time=  25.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.687 total time=  34.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.680 total time=  26.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.672 total time=  31.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.682 total time=  29.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.670 total time=  33.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.686 total time=  25.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  32.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.676 total time=  25.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.685 total time=  34.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.677 total time=  29.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.691 total time=  24.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.678 total time=  28.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.688 total time=  24.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.684 total time=  31.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.679 total time=  24.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.685 total time=  32.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.687 total time=  31.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.683 total time=  38.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.681 total time=  35.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.665 total time=  27.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.687 total time=  37.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.679 total time=  30.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.689 total time=  25.9s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.680 total time=  30.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.690 total time=  27.6s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  34.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.678 total time=  25.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.686 total time=  33.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  28.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.692 total time=  24.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.683 total time=  28.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.688 total time=  26.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.680 total time=  34.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.675 total time=  30.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  37.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.688 total time=  34.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.677 total time=  25.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.673 total time=  33.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.687 total time=  29.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.683 total time=  35.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.690 total time=  32.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.678 total time=  25.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.694 total time=  33.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  28.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  34.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.679 total time=  32.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.681 total time=  30.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.676 total time=  36.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.688 total time=  34.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.678 total time=  26.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.661 total time=  34.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.686 total time=  29.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  35.3s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.685 total time=  27.2s\n",
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      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.693 total time=  24.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.676 total time=  28.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.692 total time=  24.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.694 total time=  31.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.679 total time=  27.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.673 total time=  35.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.687 total time=  31.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.679 total time=  38.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.681 total time=  36.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.692 total time=  29.9s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  35.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.690 total time=  33.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.678 total time=  26.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.683 total time=  33.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.685 total time=  28.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  34.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.678 total time=  31.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.683 total time=  25.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  33.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.678 total time=  30.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.680 total time=  26.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.676 total time=  30.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.684 total time=  27.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.685 total time=  34.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.684 total time=  26.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.686 total time=  34.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.676 total time=  29.3s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  35.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  33.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.694 total time=  28.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  33.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  29.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.686 total time=  24.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.683 total time=  32.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.681 total time=  27.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.686 total time=  36.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.677 total time=  30.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.682 total time=  26.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.677 total time=  30.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.687 total time=  25.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.690 total time=  32.4s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.679 total time=  25.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.681 total time=  25.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.676 total time=  34.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.684 total time=  30.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.679 total time=  42.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  37.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.680 total time=  29.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.690 total time=  25.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  29.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.689 total time=  25.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.698 total time=  32.9s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.677 total time=  24.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.684 total time=  32.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.686 total time=  28.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  34.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.680 total time=  32.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.667 total time=  28.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.688 total time=  37.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.681 total time=  31.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.680 total time=  26.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.672 total time=  31.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.684 total time=  26.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.676 total time=  33.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.681 total time=  26.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.691 total time=  34.6s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  29.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.676 total time=  35.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.675 total time=  32.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.694 total time=  28.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  33.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.697 total time=  31.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.676 total time=  26.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.666 total time=  34.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.690 total time=  30.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  37.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  34.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.670 total time=  26.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.685 total time=  35.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.677 total time=  29.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.692 total time=  25.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.688 total time=  32.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.676 total time=  24.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  32.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.694 total time=  27.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.675 total time=  35.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.692 total time=  31.4s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.677 total time=  26.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  34.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.686 total time=  30.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  36.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.674 total time=  34.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.670 total time=  26.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.687 total time=  34.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  29.6s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.685 total time=  26.5s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.686 total time=  34.7s\n",
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      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.692 total time=  33.2s\n",
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      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.679 total time=  32.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.680 total time=  30.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  36.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.682 total time=  35.1s\n",
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      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.671 total time=  35.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.691 total time=  30.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.679 total time=  36.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  33.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.681 total time=  26.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  35.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.677 total time=  28.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.693 total time=  24.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.684 total time=  28.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.683 total time=  25.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.686 total time=  32.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.680 total time=  27.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.688 total time=  35.9s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.672 total time=  30.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.672 total time=  37.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  34.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.688 total time=  28.9s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  34.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.680 total time=  32.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.672 total time=  25.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.676 total time=  33.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.687 total time=  28.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  34.2s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  32.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.682 total time=  25.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  33.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.678 total time=  30.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.680 total time=  26.3s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.659 total time=  31.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.680 total time=  27.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.686 total time=  34.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.678 total time=  25.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.685 total time=  34.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.676 total time=  29.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.673 total time=  26.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.666 total time=  35.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  35.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.676 total time=  31.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.686 total time=  36.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.680 total time=  26.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.686 total time=  34.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.677 total time=  29.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.668 total time=  35.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.684 total time=  34.2s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.678 total time=  28.3s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  34.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.680 total time=  32.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.690 total time=  28.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.677 total time=  34.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.670 total time=  31.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.685 total time=  27.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.686 total time=  34.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.678 total time=  27.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.685 total time=  35.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.679 total time=  29.5s\n",
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      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.693 total time=  29.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.676 total time=  35.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.680 total time=  29.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.687 total time=  25.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.687 total time=  32.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.679 total time=  25.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.682 total time=  32.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.687 total time=  30.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.676 total time=  36.6s\n",
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      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.683 total time=  30.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.676 total time=  36.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.687 total time=  32.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.675 total time=  25.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.675 total time=  33.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.683 total time=  29.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.679 total time=  34.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.697 total time=  31.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.675 total time=  24.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  34.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.688 total time=  28.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.677 total time=  34.2s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.675 total time=  34.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.672 total time=  27.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.682 total time=  36.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  30.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.689 total time=  25.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.682 total time=  30.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.685 total time=  25.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.677 total time=  33.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.682 total time=  29.1s\n",
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      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.678 total time=  34.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.688 total time=  29.4s\n",
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      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.677 total time=  34.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.668 total time=  27.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.687 total time=  36.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  31.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.686 total time=  25.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.676 total time=  29.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.686 total time=  25.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.686 total time=  32.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.679 total time=  25.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  34.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.677 total time=  28.3s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.684 total time=  34.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.679 total time=  33.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.691 total time=  28.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.676 total time=  33.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.677 total time=  33.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.678 total time=  26.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.683 total time=  34.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.679 total time=  29.9s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.679 total time=  36.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.686 total time=  32.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.675 total time=  25.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.682 total time=  34.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.674 total time=  30.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.689 total time=  26.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.679 total time=  30.2s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.677 total time=  42.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.679 total time=  37.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.692 total time=  28.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.679 total time=  34.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.685 total time=  32.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.679 total time=  25.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.678 total time=  33.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.683 total time=  28.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  33.9s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.678 total time=  31.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.679 total time=  25.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.687 total time=  34.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.676 total time=  31.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.683 total time=  26.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.672 total time=  31.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.686 total time=  26.9s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.686 total time=  35.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.676 total time=  26.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.676 total time=  34.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.688 total time=  30.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.676 total time=  36.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.687 total time=  34.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.678 total time=  25.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.684 total time=  33.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  28.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.680 total time=  34.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  33.4s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.673 total time=  30.9s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.669 total time=  36.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.672 total time=  35.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.685 total time=  30.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.678 total time=  36.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  33.0s\n",
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      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.692 total time=  24.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.684 total time=  29.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.686 total time=  25.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.687 total time=  33.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.677 total time=  25.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.688 total time=  33.2s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.680 total time=  30.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.662 total time=  37.1s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.682 total time=  30.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.681 total time=  36.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.677 total time=  33.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.678 total time=  26.0s\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.676 total time=  30.3s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.689 total time=  27.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  34.2s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.688 total time=  26.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.691 total time=  33.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.680 total time=  27.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  34.8s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.687 total time=  28.7s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.684 total time=  34.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.679 total time=  26.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.674 total time=  36.3s\n",
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      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.667 total time=  36.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  33.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.686 total time=  28.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.681 total time=  34.5s\n",
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      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.685 total time=  24.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  31.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.676 total time=  25.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.688 total time=  34.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  28.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.681 total time=  34.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.680 total time=  34.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.684 total time=  30.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  35.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.681 total time=  33.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.678 total time=  25.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  33.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.686 total time=  28.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.677 total time=  34.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.666 total time=  26.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  34.4s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.677 total time=  30.7s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.668 total time=  41.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  37.6s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.676 total time=  29.3s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.673 total time=  35.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.678 total time=  33.5s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.691 total time=  28.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.677 total time=  34.6s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.687 total time=  31.4s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.676 total time=  24.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.684 total time=  32.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.686 total time=  28.6s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.677 total time=  34.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.686 total time=  34.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.680 total time=  28.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.687 total time=  36.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.677 total time=  31.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.671 total time=  37.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  33.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.689 total time=  29.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  35.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.688 total time=  33.6s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1400;, score=0.680 total time=  25.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  32.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.683 total time=  28.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.677 total time=  34.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.676 total time=  32.0s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.666 total time=  27.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.688 total time=  36.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.680 total time=  30.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.683 total time=  27.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.675 total time=  31.4s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.686 total time=  26.1s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.686 total time=  33.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.681 total time=  25.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.688 total time=  34.5s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  29.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.681 total time=  35.4s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.687 total time=  32.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1600;, score=0.685 total time=  28.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.678 total time=  34.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.675 total time=  31.8s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.662 total time=  27.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.679 total time=  35.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.676 total time=  30.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.662 total time=  37.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.681 total time=  34.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.686 total time=  29.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.674 total time=  35.0s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.693 total time=  33.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1400;, score=0.676 total time=  25.6s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.686 total time=  30.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.678 total time=  36.9s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.680 total time=  38.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1600;, score=0.681 total time=  34.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.682 total time=  37.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800;, score=0.689 total time=  32.6s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1400;, score=0.679 total time=  25.6s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.676 total time=  33.6s\n",
      "[CV 2/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.683 total time=  29.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.678 total time=  35.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.676 total time=  31.8s\n",
      "[CV 4/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.677 total time=  25.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.692 total time=  33.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  28.3s\n",
      "[CV 5/5] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1900;, score=0.686 total time=  35.4s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1800;, score=0.678 total time=  34.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1600;, score=0.681 total time=  31.3s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1900;, score=0.675 total time=  38.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1800;, score=0.683 total time=  35.5s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400;, score=0.682 total time=  26.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.690 total time=  36.1s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1600;, score=0.678 total time=  30.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1900;, score=0.686 total time=  35.7s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1800;, score=0.681 total time=  34.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1600;, score=0.692 total time=  28.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1900;, score=0.676 total time=  34.1s\n",
      "[CV 1/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1800;, score=0.689 total time=  31.7s\n",
      "[CV 3/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1400;, score=0.675 total time=  25.0s\n",
      "[CV 4/5] END bootstrap=True, max_depth=70, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1800;, score=0.676 total time=  32.4s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.685 total time=  30.0s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1900;, score=0.680 total time=  36.0s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.688 total time=  35.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.678 total time=  27.3s\n",
      "[CV 1/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.691 total time=  35.8s\n",
      "[CV 3/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.676 total time=  29.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.679 total time=  35.5s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.677 total time=  33.7s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.685 total time=  29.3s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1900;, score=0.678 total time=  35.3s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=2, n_estimators=1800;, score=0.686 total time=  31.9s\n",
      "[CV 5/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1400;, score=0.674 total time=  25.2s\n",
      "[CV 2/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=4, n_estimators=1900;, score=0.682 total time=  33.9s\n",
      "[CV 4/5] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=5, min_samples_split=6, n_estimators=1600;, score=0.678 total time=  28.8s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1400;, score=0.677 total time=  26.2s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=2, n_estimators=1600;, score=0.667 total time=  30.8s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1400;, score=0.692 total time=  26.5s\n",
      "[CV 2/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=4, n_estimators=1800;, score=0.686 total time=  34.1s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1400;, score=0.679 total time=  26.7s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=3, min_samples_split=6, n_estimators=1900;, score=0.691 total time=  35.4s\n",
      "[CV 3/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600;, score=0.678 total time=  29.1s\n",
      "[CV 5/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1900;, score=0.681 total time=  35.2s\n",
      "[CV 4/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=4, n_estimators=1800;, score=0.683 total time=  33.2s\n",
      "[CV 1/5] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=6, n_estimators=1600;, score=0.686 total time=  28.9s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'bootstrap': True,\n",
       " 'max_depth': 60,\n",
       " 'max_features': 'sqrt',\n",
       " 'min_samples_leaf': 5,\n",
       " 'min_samples_split': 6,\n",
       " 'n_estimators': 1900}"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.fit(X, y)\n",
    "grid_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "be3ae473",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Temp/grid_search.joblib']"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joblib.dump(grid_search, 'Temp/rf_grid_search.joblib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "c4377429",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_best_cv =  grid_search.best_estimator_\n",
    "name_of_model = \"rf_grid_search_best\"\n",
    "preds_best_grid = model_best_cv.predict(df_test)\n",
    "\n",
    "save_predictions(preds_best_grid, \"Predictions/\"+name_of_model)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e1ed36e",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# HERE JUST DO WHATEVER YOU WANT WITH THE MODELS. I DID A STRATIFIED K-FOLD ON A RANDOM FOREST\n",
    "# COMMENT OR DELETE WHATEVER YOU DON'T WANT TO USE AND MAKE YOUR OWN MODELS TO TEST AND ALL THAT SHIT\n",
    "\n",
    "#X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "# skf = StratifiedKFold(n_splits = 3)\n",
    "# score_list = []\n",
    "# models = []\n",
    "# #Stratified fold to keep the data imbalance while training\n",
    "# #Train 3 times to simulate a 3 way cross-validation\n",
    "# for train, test in skf.split(df_train, y):\n",
    "#     print('train -  {}   |   test -  {}'.format(np.bincount(y[train]), np.bincount(y[test])))\n",
    "#     train_x = df_train.iloc[train]\n",
    "#     train_y = y.iloc[train]\n",
    "#     test_x = df_train.iloc[test]\n",
    "#     test_y = y.iloc[test]\n",
    "#     #CREATE THE MODELS HERE IF POSSIBLE\n",
    "    \n",
    "#     #Random Forest\n",
    "#     clf = RandomForestClassifier(random_state = 0)\n",
    "#     clf.fit(train_x, train_y)\n",
    "#     y_pred = clf.predict(test_x)\n",
    "#     print(compute_metrics(y_pred, test_y))\n",
    "    \n",
    "#     #SAVE BEST SCORES AND BEST MODELS TO TEST ON THE DATA LATER.\n",
    "#     score_list.append(clf.score(test_x,test_y))\n",
    "#     models.append(clf)\n",
    "\n",
    "# #Check Metrics attained\n",
    "# best_model_index = score_list.index(max(score_list))\n",
    "# preds = models[best_model_index].predict(df_test)\n",
    "\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.ensemble import RandomForestClassifier, VotingClassifier\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "clf1 = RandomForestClassifier( random_state=1)\n",
    "\n",
    "clf2 = make_pipeline(StandardScaler(), SVC(gamma='auto', probability=True))\n",
    "\n",
    "clf3 = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0,\n",
    "    max_depth=1, random_state=0)\n",
    "\n",
    "print(\"Fitting Classifiers\")\n",
    "eclf1 = VotingClassifier(estimators=[\n",
    "        ('rf', clf1), ('svm', clf2), ('xgb', clf3)], voting='hard')\n",
    "\n",
    "\n",
    "\n",
    "eclf2 = VotingClassifier(estimators=[\n",
    "        ('rf', clf1), ('svm', clf2), ('xgb', clf3)],\n",
    "        voting='soft')\n",
    "\n",
    "\n",
    "\n",
    "print(\"Hard Voting \")\n",
    "hard_scores = cross_val_score(eclf1, X, y, cv=10)\n",
    "print(\"Soft Voting\")\n",
    "soft_scores = cross_val_score(eclf2, X, y, cv=10)\n",
    "\n",
    "print(\"aux stop\")\n",
    "\n",
    "\n",
    "import joblib\n",
    "name_of_model = \"rf+svm+xgboost\"\n",
    "\n",
    "joblib.dump(hard_scores, \"Temp/\"+name_of_model+\"_hard_scores\"+\".joblib\")\n",
    "joblib.dump(hard_scores, \"Temp/\"+ name_of_model+\"_soft_scores\"+ \".joblib\")\n",
    "\n",
    "print(\"hard voting\", hard_scores.mean())\n",
    "print(\"soft voting\", soft_scores.mean())\n",
    "\n",
    "print(\"aux stop\")\n",
    "\n",
    "\n",
    "\n",
    "eclf1.fit(X, y)\n",
    "preds_hard = eclf1.predict(df_test)\n",
    "save_predictions(preds_hard, \"Predictions/\"+name_of_model+\"_hard\")\n",
    "\n",
    "eclf2.fit(X, y)\n",
    "preds_soft = eclf2.predict(df_test)\n",
    "save_predictions(preds_soft, \"Predictions/\"+ name_of_model+\"_soft\")\n",
    "\n",
    "\n",
    "\n"
   ]
  }
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