Scikit-learn LIBRARY - Car Sales Project using Pipeline #final #coverup.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3fb2f075",
   "metadata": {},
   "source": [
    "## Car Sales Project - `predict price of car`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4748a7d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports necessary libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "00b3003b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Make</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Odometer (KM)</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Honda</td>\n",
       "      <td>White</td>\n",
       "      <td>35431.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15323.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BMW</td>\n",
       "      <td>Blue</td>\n",
       "      <td>192714.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>19943.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Honda</td>\n",
       "      <td>White</td>\n",
       "      <td>84714.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>28343.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>White</td>\n",
       "      <td>154365.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13434.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>Blue</td>\n",
       "      <td>181577.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>14043.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Black</td>\n",
       "      <td>35820.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>32042.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>White</td>\n",
       "      <td>155144.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5716.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>Blue</td>\n",
       "      <td>66604.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>31570.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Honda</td>\n",
       "      <td>White</td>\n",
       "      <td>215883.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4001.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Blue</td>\n",
       "      <td>248360.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12732.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Make Colour  Odometer (KM)  Doors    Price\n",
       "0     Honda  White        35431.0    4.0  15323.0\n",
       "1       BMW   Blue       192714.0    5.0  19943.0\n",
       "2     Honda  White        84714.0    4.0  28343.0\n",
       "3    Toyota  White       154365.0    4.0  13434.0\n",
       "4    Nissan   Blue       181577.0    3.0  14043.0\n",
       "..      ...    ...            ...    ...      ...\n",
       "995  Toyota  Black        35820.0    4.0  32042.0\n",
       "996     NaN  White       155144.0    3.0   5716.0\n",
       "997  Nissan   Blue        66604.0    4.0  31570.0\n",
       "998   Honda  White       215883.0    4.0   4001.0\n",
       "999  Toyota   Blue       248360.0    4.0  12732.0\n",
       "\n",
       "[1000 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('data/car-sales-extended-missing-data.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f3dd4af7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Make              object\n",
       "Colour            object\n",
       "Odometer (KM)    float64\n",
       "Doors            float64\n",
       "Price            float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check types of data\n",
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "83f30141",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Make             49\n",
       "Colour           50\n",
       "Odometer (KM)    50\n",
       "Doors            50\n",
       "Price            50\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check null values of data\n",
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f6947ae",
   "metadata": {},
   "source": [
    "**KEY POINTS**\n",
    "* All data should be `numerical`\n",
    "* There should be no `missing values`\n",
    "* Manipulate the `test` set the same as the `training` set\n",
    "* Never `test` on data you've `trained` on\n",
    "* Tune `hyperparameters` on validation set OR use `cross-validation`\n",
    "* One best performance `metric` doesn't mean the best model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc24498a",
   "metadata": {},
   "source": [
    "***Process of job*** `all in one cell`\n",
    "\n",
    "1. Fill missing data\n",
    "2. Convert data to numbers\n",
    "3. Build a model on the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "11c824df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.22188417408787875"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting data ready\n",
    "import pandas as pd\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "# Modelling\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "\n",
    "# Setup random seed\n",
    "import numpy as np\n",
    "np.random.seed(42)\n",
    "\n",
    "# import data and drop rows with missing labels\n",
    "data = pd.read_csv(\"data/car-sales-extended-missing-data.csv\")\n",
    "data.dropna(subset=[\"Price\"], inplace=True)\n",
    "\n",
    "# define different features and transformer pipeline\n",
    "categorical_features = [\"Make\", \"Colour\"]\n",
    "categorical_transformer = Pipeline(steps=[\n",
    "    (\"imputer\", SimpleImputer(strategy=\"constant\", fill_value=\"missing\")),\n",
    "    (\"onehot\", OneHotEncoder(handle_unknown=\"ignore\"))])\n",
    "\n",
    "door_feature = [\"Doors\"]\n",
    "door_transformer = Pipeline(steps=[\n",
    "    (\"imputer\", SimpleImputer(strategy=\"constant\", fill_value=4))])\n",
    "\n",
    "numeric_features = [\"Odometer (KM)\"]\n",
    "numeric_transformer = Pipeline(steps=[\n",
    "    (\"imputer\", SimpleImputer(strategy=\"mean\"))\n",
    "])\n",
    "\n",
    "# Setup preprocessing steps (fill missing values, then convert to numbers)\n",
    "preprocessor = ColumnTransformer(\n",
    "                            transformers=[\n",
    "                                    (\"cat\", categorical_transformer , categorical_features),\n",
    "                                    (\"door\", door_transformer, door_feature),\n",
    "                                    (\"num\", numeric_transformer, numeric_features)\n",
    "                            ])\n",
    "\n",
    "# Creating a preprocessing and modelling pipeline\n",
    "model = Pipeline(steps=[(\"preprocessor\", preprocessor),\n",
    "                        (\"model\", RandomForestRegressor())])\n",
    "\n",
    "# Split data\n",
    "X = data.drop(\"Price\", axis=1)\n",
    "y = data[\"Price\"]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n",
    "\n",
    "# Fit and score the model\n",
    "model.fit(X_train, y_train)\n",
    "model.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ef389ee",
   "metadata": {},
   "source": [
    "#### `GridSearchCV` or `RandomizedSearchCV` with `Pipeline`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c2e6b3f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# use gridsearchCV with our regression Pipeline\n",
    "pipe_grid = {\n",
    "    \"preprocessor__num__imputer__strategy\": [\"mean\", \"median\"],\n",
    "    \"model__n_estimators\": [10],\n",
    "    \"model__max_depth\": [None, 5],\n",
    "    \"model__max_features\": [\"sqrt\"],\n",
    "    \"model__min_samples_split\": [2, 4]\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "57c1ca5f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 640 candidates, totalling 3200 fits\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=None, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=5, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=10, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=20, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=30, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=60, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=90, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=2, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=4, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=6, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=8, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.3s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=10, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.2s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=12, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=14, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=16, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=18, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=10, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=50, preprocessor__num__imputer__strategy=median; total time=   0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=mean; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=100, preprocessor__num__imputer__strategy=median; total time=   0.0s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=mean; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n",
      "[CV] END model__max_depth=120, model__max_features=sqrt, model__min_samples_split=20, model__n_estimators=200, preprocessor__num__imputer__strategy=median; total time=   0.1s\n"
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     "data": {
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       "<style>#sk-container-id-3 {color: black;background-color: white;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=5,\n",
       "             estimator=Pipeline(steps=[(&#x27;preprocessor&#x27;,\n",
       "                                        ColumnTransformer(transformers=[(&#x27;cat&#x27;,\n",
       "                                                                         Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                                          SimpleImputer(fill_value=&#x27;missing&#x27;,\n",
       "                                                                                                        strategy=&#x27;constant&#x27;)),\n",
       "                                                                                         (&#x27;onehot&#x27;,\n",
       "                                                                                          OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),\n",
       "                                                                         [&#x27;Make&#x27;,\n",
       "                                                                          &#x27;Colour&#x27;]),\n",
       "                                                                        (&#x27;door&#x27;,\n",
       "                                                                         Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                                          SimpleImputer(fill_value=4,\n",
       "                                                                                                        strategy=&#x27;constant&#x27;))]),\n",
       "                                                                         [&#x27;Doors&#x27;])...\n",
       "                                                                         Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                                          SimpleImputer())]),\n",
       "                                                                         [&#x27;Odometer &#x27;\n",
       "                                                                          &#x27;(KM)&#x27;])])),\n",
       "                                       (&#x27;model&#x27;, RandomForestRegressor())]),\n",
       "             param_grid={&#x27;model__max_depth&#x27;: [None, 5, 10, 20, 30, 60, 90, 120],\n",
       "                         &#x27;model__max_features&#x27;: [&#x27;sqrt&#x27;],\n",
       "                         &#x27;model__min_samples_split&#x27;: [2, 4, 6, 8, 10, 12, 14,\n",
       "                                                      16, 18, 20],\n",
       "                         &#x27;model__n_estimators&#x27;: [10, 50, 100, 200],\n",
       "                         &#x27;preprocessor__num__imputer__strategy&#x27;: [&#x27;mean&#x27;,\n",
       "                                                                  &#x27;median&#x27;]},\n",
       "             verbose=2)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-23\" type=\"checkbox\" ><label for=\"sk-estimator-id-23\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(cv=5,\n",
       "             estimator=Pipeline(steps=[(&#x27;preprocessor&#x27;,\n",
       "                                        ColumnTransformer(transformers=[(&#x27;cat&#x27;,\n",
       "                                                                         Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                                          SimpleImputer(fill_value=&#x27;missing&#x27;,\n",
       "                                                                                                        strategy=&#x27;constant&#x27;)),\n",
       "                                                                                         (&#x27;onehot&#x27;,\n",
       "                                                                                          OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),\n",
       "                                                                         [&#x27;Make&#x27;,\n",
       "                                                                          &#x27;Colour&#x27;]),\n",
       "                                                                        (&#x27;door&#x27;,\n",
       "                                                                         Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                                          SimpleImputer(fill_value=4,\n",
       "                                                                                                        strategy=&#x27;constant&#x27;))]),\n",
       "                                                                         [&#x27;Doors&#x27;])...\n",
       "                                                                         Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                                          SimpleImputer())]),\n",
       "                                                                         [&#x27;Odometer &#x27;\n",
       "                                                                          &#x27;(KM)&#x27;])])),\n",
       "                                       (&#x27;model&#x27;, RandomForestRegressor())]),\n",
       "             param_grid={&#x27;model__max_depth&#x27;: [None, 5, 10, 20, 30, 60, 90, 120],\n",
       "                         &#x27;model__max_features&#x27;: [&#x27;sqrt&#x27;],\n",
       "                         &#x27;model__min_samples_split&#x27;: [2, 4, 6, 8, 10, 12, 14,\n",
       "                                                      16, 18, 20],\n",
       "                         &#x27;model__n_estimators&#x27;: [10, 50, 100, 200],\n",
       "                         &#x27;preprocessor__num__imputer__strategy&#x27;: [&#x27;mean&#x27;,\n",
       "                                                                  &#x27;median&#x27;]},\n",
       "             verbose=2)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-24\" type=\"checkbox\" ><label for=\"sk-estimator-id-24\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;preprocessor&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;cat&#x27;,\n",
       "                                                  Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                   SimpleImputer(fill_value=&#x27;missing&#x27;,\n",
       "                                                                                 strategy=&#x27;constant&#x27;)),\n",
       "                                                                  (&#x27;onehot&#x27;,\n",
       "                                                                   OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),\n",
       "                                                  [&#x27;Make&#x27;, &#x27;Colour&#x27;]),\n",
       "                                                 (&#x27;door&#x27;,\n",
       "                                                  Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                   SimpleImputer(fill_value=4,\n",
       "                                                                                 strategy=&#x27;constant&#x27;))]),\n",
       "                                                  [&#x27;Doors&#x27;]),\n",
       "                                                 (&#x27;num&#x27;,\n",
       "                                                  Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                                   SimpleImputer())]),\n",
       "                                                  [&#x27;Odometer (KM)&#x27;])])),\n",
       "                (&#x27;model&#x27;, RandomForestRegressor())])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-25\" type=\"checkbox\" ><label for=\"sk-estimator-id-25\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">preprocessor: ColumnTransformer</label><div class=\"sk-toggleable__content\"><pre>ColumnTransformer(transformers=[(&#x27;cat&#x27;,\n",
       "                                 Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                  SimpleImputer(fill_value=&#x27;missing&#x27;,\n",
       "                                                                strategy=&#x27;constant&#x27;)),\n",
       "                                                 (&#x27;onehot&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;))]),\n",
       "                                 [&#x27;Make&#x27;, &#x27;Colour&#x27;]),\n",
       "                                (&#x27;door&#x27;,\n",
       "                                 Pipeline(steps=[(&#x27;imputer&#x27;,\n",
       "                                                  SimpleImputer(fill_value=4,\n",
       "                                                                strategy=&#x27;constant&#x27;))]),\n",
       "                                 [&#x27;Doors&#x27;]),\n",
       "                                (&#x27;num&#x27;,\n",
       "                                 Pipeline(steps=[(&#x27;imputer&#x27;, SimpleImputer())]),\n",
       "                                 [&#x27;Odometer (KM)&#x27;])])</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-26\" type=\"checkbox\" ><label for=\"sk-estimator-id-26\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">cat</label><div class=\"sk-toggleable__content\"><pre>[&#x27;Make&#x27;, &#x27;Colour&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-27\" type=\"checkbox\" ><label for=\"sk-estimator-id-27\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer(fill_value=&#x27;missing&#x27;, strategy=&#x27;constant&#x27;)</pre></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-28\" type=\"checkbox\" ><label for=\"sk-estimator-id-28\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">OneHotEncoder</label><div class=\"sk-toggleable__content\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-29\" type=\"checkbox\" ><label for=\"sk-estimator-id-29\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">door</label><div class=\"sk-toggleable__content\"><pre>[&#x27;Doors&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-30\" type=\"checkbox\" ><label for=\"sk-estimator-id-30\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer(fill_value=4, strategy=&#x27;constant&#x27;)</pre></div></div></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-31\" type=\"checkbox\" ><label for=\"sk-estimator-id-31\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">num</label><div class=\"sk-toggleable__content\"><pre>[&#x27;Odometer (KM)&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-32\" type=\"checkbox\" ><label for=\"sk-estimator-id-32\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer()</pre></div></div></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-33\" type=\"checkbox\" ><label for=\"sk-estimator-id-33\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor()</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=5,\n",
       "             estimator=Pipeline(steps=[('preprocessor',\n",
       "                                        ColumnTransformer(transformers=[('cat',\n",
       "                                                                         Pipeline(steps=[('imputer',\n",
       "                                                                                          SimpleImputer(fill_value='missing',\n",
       "                                                                                                        strategy='constant')),\n",
       "                                                                                         ('onehot',\n",
       "                                                                                          OneHotEncoder(handle_unknown='ignore'))]),\n",
       "                                                                         ['Make',\n",
       "                                                                          'Colour']),\n",
       "                                                                        ('door',\n",
       "                                                                         Pipeline(steps=[('imputer',\n",
       "                                                                                          SimpleImputer(fill_value=4,\n",
       "                                                                                                        strategy='constant'))]),\n",
       "                                                                         ['Doors'])...\n",
       "                                                                         Pipeline(steps=[('imputer',\n",
       "                                                                                          SimpleImputer())]),\n",
       "                                                                         ['Odometer '\n",
       "                                                                          '(KM)'])])),\n",
       "                                       ('model', RandomForestRegressor())]),\n",
       "             param_grid={'model__max_depth': [None, 5, 10, 20, 30, 60, 90, 120],\n",
       "                         'model__max_features': ['sqrt'],\n",
       "                         'model__min_samples_split': [2, 4, 6, 8, 10, 12, 14,\n",
       "                                                      16, 18, 20],\n",
       "                         'model__n_estimators': [10, 50, 100, 200],\n",
       "                         'preprocessor__num__imputer__strategy': ['mean',\n",
       "                                                                  'median']},\n",
       "             verbose=2)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_model = GridSearchCV(model, pipe_grid, cv=5, verbose=2)\n",
    "gs_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2afb17d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'model__max_depth': 5,\n",
       " 'model__max_features': 'sqrt',\n",
       " 'model__min_samples_split': 2,\n",
       " 'model__n_estimators': 10,\n",
       " 'preprocessor__num__imputer__strategy': 'mean'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_model.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a48127fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.31269067075414847"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gs_model.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfb4d1e5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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