automatic_classification-refactored.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6751fcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     /home/derickrentz/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     /home/derickrentz/nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer  \n",
    "from sklearn.model_selection import train_test_split \n",
    "import nltk \n",
    "import joblib\n",
    "import string\n",
    "import re\n",
    "from flask import Flask\n",
    "from flask import request\n",
    "%matplotlib inline\n",
    "pd.set_option('display.max_colwidth', 100)\n",
    "nltk.download('stopwords')\n",
    "nltk.download('wordnet')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "758d43b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load dataset\n",
    "def load_data():\n",
    "    data = pd.read_csv('gold_reddit_corpus_agree.csv')\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0b6dbc3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "reddit_df = load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "380995b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='cls', ylabel='count'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x = 'cls', data = reddit_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8132c66f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Insert random platitude here.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>It's like this in Canada. Don't ever call a helpline. Their thereshold for calling the cops is p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>It has never occured to me before now that this also a method of suicide (although this was a fl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Obese people, regardless of their gender, make me shit.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The best way to spot a hyper-macho is knowing how much you love your mother. The most dangerous ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>I'm gonna end it all\\nEverything is getting worse and worse. My parents value material things mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>757 ppl online\\nits comforting to know that theres ppl other than me who feel this way but why a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>I've meticulously planned everything to the last detail, but whenever they ask me if I have a pl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>Fuck me\\nI just want to go to sleep, and never wake up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>Why do so many people get to die by accident and for me to die I have to kill myself.\\nFuck</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>273 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                                    text\n",
       "0                                                                         Insert random platitude here. \n",
       "1    It's like this in Canada. Don't ever call a helpline. Their thereshold for calling the cops is p...\n",
       "2    It has never occured to me before now that this also a method of suicide (although this was a fl...\n",
       "3                                                Obese people, regardless of their gender, make me shit.\n",
       "4    The best way to spot a hyper-macho is knowing how much you love your mother. The most dangerous ...\n",
       "..                                                                                                   ...\n",
       "268  I'm gonna end it all\\nEverything is getting worse and worse. My parents value material things mo...\n",
       "269  757 ppl online\\nits comforting to know that theres ppl other than me who feel this way but why a...\n",
       "270  I've meticulously planned everything to the last detail, but whenever they ask me if I have a pl...\n",
       "271                                               Fuck me\\nI just want to go to sleep, and never wake up\n",
       "272          Why do so many people get to die by accident and for me to die I have to kill myself.\\nFuck\n",
       "\n",
       "[273 rows x 1 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(reddit_df[['text']])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d1e6f7e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_text(text):\n",
    "    ps = nltk.PorterStemmer()\n",
    "    stopword = nltk.corpus.stopwords.words('english')\n",
    "    stopword.extend(['http', 'https'])\n",
    "    \n",
    "    text_lc = \"\".join([word.lower() for word in text if word not in string.punctuation]) # remove puntuation\n",
    "    text_rc = re.sub('[0-9]+', '', text_lc)\n",
    "    tokens = re.split('\\W+', text_rc)    # tokenization\n",
    "    text = [ps.stem(word) for word in tokens if word not in stopword]  # remove stopwords and stemming\n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0074e226",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "273 Number of texts has 350 words\n"
     ]
    }
   ],
   "source": [
    "tfidfconverter = TfidfVectorizer(analyzer=clean_text, max_features=350)  \n",
    "X = tfidfconverter.fit_transform(df['text'])\n",
    "print('{} Number of texts has {} words'.format(X.shape[0], X.shape[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3b70d28e",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.261836</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.258839</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.433422</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.263620</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>0.182036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 350 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              abl  absolut  accept  act  actual  age  ago  aliv  almost  ...  \\\n",
       "0   1.000000  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "1   0.261836  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "2   0.258839  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "3   0.000000  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "4   0.000000  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "..       ...  ...      ...     ...  ...     ...  ...  ...   ...     ...  ...   \n",
       "95  0.000000  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "96  0.000000  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "97  0.263620  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "98  0.000000  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "99  0.182036  0.0      0.0     0.0  0.0     0.0  0.0  0.0   0.0     0.0  ...   \n",
       "\n",
       "    worthless     would  wouldnt  write  wrong   xb  year  yet  young  your  \n",
       "0         0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "1         0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "2         0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "3         0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "4         0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "..        ...       ...      ...    ...    ...  ...   ...  ...    ...   ...  \n",
       "95        0.0  0.433422      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "96        0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "97        0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "98        0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "99        0.0  0.000000      0.0    0.0    0.0  0.0   0.0  0.0    0.0   0.0  \n",
       "\n",
       "[100 rows x 350 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_vect_df = pd.DataFrame(X.toarray(), columns=tfidfconverter.get_feature_names())\n",
    "count_vect_df.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bea791e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Risk:  142\n",
      "No risk:  76\n"
     ]
    }
   ],
   "source": [
    "# Getting cls column\n",
    "y = pd.DataFrame(reddit_df['cls']).values.ravel()\n",
    "# y = y.values.ravel()\n",
    "\n",
    "# Splitting train/test data\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)\n",
    "\n",
    "risk_count = 0\n",
    "no_risk_count = 0\n",
    "\n",
    "# Prints training data split\n",
    "for i in y_train:\n",
    "    if i == 'Risk':\n",
    "        risk_count += 1\n",
    "    else:\n",
    "        no_risk_count += 1\n",
    "\n",
    "print (\"Risk: \", risk_count)\n",
    "print (\"No risk: \", no_risk_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6ca33918",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(random_state=0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the model with training data\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "text_classifier = RandomForestClassifier(n_estimators=100, random_state=0)  \n",
    "text_classifier.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "447f4cf9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000], 'max_features': ['auto', 'sqrt'], 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, None], 'min_samples_split': [2, 5, 10], 'min_samples_leaf': [1, 2, 4], 'bootstrap': [True, False]}\n",
      "Fitting 3 folds for each of 100 candidates, totalling 300 fits\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1800; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   1.5s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   1.9s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.6s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'n_estimators': 400, 'min_samples_split': 2, 'min_samples_leaf': 1, 'max_features': 'sqrt', 'max_depth': None, 'bootstrap': False}\n",
      "[[10  4]\n",
      " [ 3 38]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "     No risk       0.77      0.71      0.74        14\n",
      "        Risk       0.90      0.93      0.92        41\n",
      "\n",
      "    accuracy                           0.87        55\n",
      "   macro avg       0.84      0.82      0.83        55\n",
      "weighted avg       0.87      0.87      0.87        55\n",
      "\n",
      "0.8727272727272727\n",
      "Fitting 3 folds for each of 270 candidates, totalling 810 fits\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=110, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=1400; total time=   1.8s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1600; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   2.2s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=True, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1800; total time=   1.8s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=1400; total time=   1.5s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=110, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1400; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1200; total time=   1.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400; total time=   1.4s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=110, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1800; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=50, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   2.0s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.2s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.2s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=2000; total time=   2.6s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=110, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1800; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   1.6s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=110, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1400; total time=   1.5s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   1.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.0s\n",
      "[CV] END bootstrap=True, max_depth=70, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1600; total time=   1.7s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1800; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=2000; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   2.6s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=True, max_depth=70, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1400; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.2s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   1.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.4s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1800; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   1.5s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=200; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1200; total time=   1.2s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=1400; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1800; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=110, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1800; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=1400; total time=   1.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=50, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=200; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=200; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1800; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=True, max_depth=70, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1400; total time=   1.9s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   1.2s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=1400; total time=   1.8s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=1200; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=True, max_depth=110, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=1400; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400; total time=   1.4s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=200; total time=   0.2s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=30, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=1400; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=2000; total time=   2.0s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   2.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1200; total time=   1.2s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   1.9s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1800; total time=   2.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.0s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   1.8s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   2.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1000; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=110, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.7s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600; total time=   2.0s\n",
      "[CV] END bootstrap=True, max_depth=70, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1600; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1800; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=2000; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1800; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=110, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1800; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=1400; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=1200; total time=   1.7s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=110, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=200; total time=   0.3s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.0s\n",
      "[CV] END bootstrap=True, max_depth=70, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=1200; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=50, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=800; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=110, max_features=sqrt, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1400; total time=   1.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=1000; total time=   1.0s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=5, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1000; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=2000; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   1.9s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=1400; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=100, max_features=auto, min_samples_leaf=4, min_samples_split=10, n_estimators=2000; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=800; total time=   1.2s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=800; total time=   1.2s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   2.3s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1400; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   2.0s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1400; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   1.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   1.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=auto, min_samples_leaf=4, min_samples_split=2, n_estimators=1800; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   1.7s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1000; total time=   1.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=True, max_depth=70, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1400; total time=   1.8s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=90, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=4, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=10, n_estimators=1000; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   1.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=2000; total time=   2.6s\n",
      "[CV] END bootstrap=False, max_depth=10, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1600; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=80, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=True, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=1800; total time=   2.4s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=True, max_depth=20, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=1200; total time=   1.6s\n",
      "[CV] END bootstrap=True, max_depth=90, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=4, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=20, max_features=auto, min_samples_leaf=1, min_samples_split=2, n_estimators=1800; total time=   2.1s\n",
      "[CV] END bootstrap=True, max_depth=10, max_features=auto, min_samples_leaf=1, min_samples_split=5, n_estimators=1600; total time=   2.1s\n",
      "[CV] END bootstrap=False, max_depth=None, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=1200; total time=   1.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=2000; total time=   2.2s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=2000; total time=   2.7s\n",
      "[CV] END bootstrap=True, max_depth=100, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.6s\n",
      "[CV] END bootstrap=True, max_depth=110, max_features=sqrt, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=30, max_features=sqrt, min_samples_leaf=4, min_samples_split=2, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=auto, min_samples_leaf=2, min_samples_split=10, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=40, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=50, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score\n",
    "\n",
    "# Number of trees in random forest\n",
    "n_estimators = [int(x) for x in np.linspace(start = 200, stop = 2000, num = 10)]\n",
    "# Number of features to consider at every split\n",
    "max_features = ['auto', 'sqrt']\n",
    "# Maximum number of levels in tree\n",
    "max_depth = [int(x) for x in np.linspace(10, 110, num = 11)]\n",
    "max_depth.append(None)\n",
    "# Minimum number of samples required to split a node\n",
    "min_samples_split = [2, 5, 10]\n",
    "# Minimum number of samples required at each leaf node\n",
    "min_samples_leaf = [1, 2, 4]\n",
    "# Method of selecting samples for training each tree\n",
    "bootstrap = [True, False]\n",
    "# Create the random grid\n",
    "random_grid = {'n_estimators': n_estimators,\n",
    "               'max_features': max_features,\n",
    "               'max_depth': max_depth,\n",
    "               'min_samples_split': min_samples_split,\n",
    "               'min_samples_leaf': min_samples_leaf,\n",
    "               'bootstrap': bootstrap}\n",
    "\n",
    "print(random_grid)\n",
    "\n",
    "# Instantiate the grid search model\n",
    "rf = RandomForestClassifier()\n",
    "\n",
    "# Random search of parameters, using 3 fold cross validation, \n",
    "# search across 100 different combinations, and use all available cores\n",
    "rf_random = RandomizedSearchCV(estimator = rf, param_distributions = random_grid, n_iter = 100, cv = 3, verbose=2, random_state=42, n_jobs = -1)\n",
    "# Fit the random search model\n",
    "rf_random.fit(X_train, y_train)\n",
    "\n",
    "print(rf_random.best_params_)\n",
    "# {'n_estimators': 600, 'min_samples_split': 5, 'min_samples_leaf': 1, 'max_features': 'sqrt', 'max_depth': 60, 'bootstrap': False}\n",
    "\n",
    "best_random = rf_random.best_estimator_\n",
    "\n",
    "best_random_predictions = best_random.predict(X_test)\n",
    "\n",
    "# Printing best random model metrics\n",
    "\n",
    "print(confusion_matrix(y_test,best_random_predictions))  \n",
    "print(classification_report(y_test,best_random_predictions))  \n",
    "print(accuracy_score(y_test, best_random_predictions))\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "# Create the parameter grid based on the results of random search \n",
    "# param_grid = {\n",
    "#     'bootstrap': [True],\n",
    "#     'max_depth': [80, 90, 100, 110],\n",
    "#     'max_features': [2, 3],\n",
    "#     'min_samples_leaf': [3, 4, 5],\n",
    "#     'min_samples_split': [8, 10, 12],\n",
    "#     'n_estimators': [100, 200, 300, 1000]\n",
    "# }\n",
    "\n",
    "param_grid = {\n",
    "    'n_estimators': [300,400,500,600,800,100], \n",
    "    'min_samples_split': [3,5,7], \n",
    "    'min_samples_leaf': [1,2,3], \n",
    "    'max_features': ['sqrt'], \n",
    "    'max_depth': [40,50,60,70,80], \n",
    "    'bootstrap': [False]\n",
    "}\n",
    "\n",
    "grid_search = GridSearchCV(estimator = rf, param_grid = param_grid, \n",
    "                          cv = 3, n_jobs = -1, verbose = 2)\n",
    "\n",
    "# Fit the grid search to the data\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "grid_search.best_params_\n",
    "best_grid = grid_search.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4ae534d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Risk' 'Risk' 'Risk' 'Risk' 'Risk' 'Risk' 'No risk' 'Risk' 'No risk'\n",
      " 'Risk' 'Risk' 'Risk' 'Risk' 'Risk' 'No risk' 'Risk' 'No risk' 'Risk'\n",
      " 'Risk' 'Risk' 'No risk' 'Risk' 'No risk' 'Risk' 'No risk' 'No risk'\n",
      " 'No risk' 'Risk' 'Risk' 'Risk' 'Risk' 'Risk' 'Risk' 'Risk' 'No risk'\n",
      " 'Risk' 'Risk' 'No risk' 'No risk' 'Risk' 'No risk' 'Risk' 'Risk' 'Risk'\n",
      " 'No risk' 'Risk' 'Risk' 'Risk' 'Risk' 'No risk' 'Risk' 'Risk' 'Risk'\n",
      " 'Risk' 'Risk']\n",
      "[[0.3  0.7 ]\n",
      " [0.36 0.64]\n",
      " [0.22 0.78]\n",
      " [0.15 0.85]\n",
      " [0.17 0.83]\n",
      " [0.13 0.87]\n",
      " [0.82 0.18]\n",
      " [0.23 0.77]\n",
      " [0.52 0.48]\n",
      " [0.17 0.83]\n",
      " [0.37 0.63]\n",
      " [0.19 0.81]\n",
      " [0.2  0.8 ]\n",
      " [0.11 0.89]\n",
      " [0.78 0.22]\n",
      " [0.16 0.84]\n",
      " [0.51 0.49]\n",
      " [0.19 0.81]\n",
      " [0.2  0.8 ]\n",
      " [0.29 0.71]\n",
      " [0.91 0.09]\n",
      " [0.19 0.81]\n",
      " [0.53 0.47]\n",
      " [0.25 0.75]\n",
      " [0.51 0.49]\n",
      " [0.99 0.01]\n",
      " [0.74 0.26]\n",
      " [0.19 0.81]\n",
      " [0.47 0.53]\n",
      " [0.25 0.75]\n",
      " [0.2  0.8 ]\n",
      " [0.08 0.92]\n",
      " [0.08 0.92]\n",
      " [0.14 0.86]\n",
      " [0.86 0.14]\n",
      " [0.22 0.78]\n",
      " [0.23 0.77]\n",
      " [0.93 0.07]\n",
      " [0.9  0.1 ]\n",
      " [0.22 0.78]\n",
      " [0.5  0.5 ]\n",
      " [0.32 0.68]\n",
      " [0.46 0.54]\n",
      " [0.09 0.91]\n",
      " [1.   0.  ]\n",
      " [0.28 0.72]\n",
      " [0.29 0.71]\n",
      " [0.25 0.75]\n",
      " [0.25 0.75]\n",
      " [0.51 0.49]\n",
      " [0.2  0.8 ]\n",
      " [0.22 0.78]\n",
      " [0.34 0.66]\n",
      " [0.2  0.8 ]\n",
      " [0.21 0.79]]\n",
      "[[0.2395     0.7605    ]\n",
      " [0.32533333 0.67466667]\n",
      " [0.22916667 0.77083333]\n",
      " [0.11566667 0.88433333]\n",
      " [0.10411111 0.89588889]\n",
      " [0.16155556 0.83844444]\n",
      " [0.85111111 0.14888889]\n",
      " [0.20883333 0.79116667]\n",
      " [0.54155556 0.45844444]\n",
      " [0.10911111 0.89088889]\n",
      " [0.30577778 0.69422222]\n",
      " [0.1785     0.8215    ]\n",
      " [0.15227778 0.84772222]\n",
      " [0.08461111 0.91538889]\n",
      " [0.83061111 0.16938889]\n",
      " [0.14655556 0.85344444]\n",
      " [0.44222222 0.55777778]\n",
      " [0.11411111 0.88588889]\n",
      " [0.15222222 0.84777778]\n",
      " [0.23461111 0.76538889]\n",
      " [0.90405556 0.09594444]\n",
      " [0.11483333 0.88516667]\n",
      " [0.60027778 0.39972222]\n",
      " [0.2805     0.7195    ]\n",
      " [0.46205556 0.53794444]\n",
      " [0.99155556 0.00844444]\n",
      " [0.6745     0.3255    ]\n",
      " [0.10261111 0.89738889]\n",
      " [0.42972222 0.57027778]\n",
      " [0.14838889 0.85161111]\n",
      " [0.17583333 0.82416667]\n",
      " [0.15716667 0.84283333]\n",
      " [0.12911111 0.87088889]\n",
      " [0.08244444 0.91755556]\n",
      " [0.88772222 0.11227778]\n",
      " [0.12555556 0.87444444]\n",
      " [0.22538889 0.77461111]\n",
      " [0.95861111 0.04138889]\n",
      " [0.94855556 0.05144444]\n",
      " [0.23861111 0.76138889]\n",
      " [0.45138889 0.54861111]\n",
      " [0.25061111 0.74938889]\n",
      " [0.38105556 0.61894444]\n",
      " [0.07533333 0.92466667]\n",
      " [0.99377778 0.00622222]\n",
      " [0.23327778 0.76672222]\n",
      " [0.335      0.665     ]\n",
      " [0.17927778 0.82072222]\n",
      " [0.22961111 0.77038889]\n",
      " [0.54544444 0.45455556]\n",
      " [0.19366667 0.80633333]\n",
      " [0.17094444 0.82905556]\n",
      " [0.28061111 0.71938889]\n",
      " [0.19777778 0.80222222]\n",
      " [0.23138889 0.76861111]]\n"
     ]
    }
   ],
   "source": [
    "# Doing predictions with test data\n",
    "predictions = text_classifier.predict(X_test)\n",
    "predictions_proba = text_classifier.predict_proba(X_test)\n",
    "best_model_predictions_proba = best_grid.predict_proba(X_test)\n",
    "\n",
    "print (predictions)\n",
    "print (predictions_proba)\n",
    "print (best_model_predictions_proba)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9b349191",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Black flags: 3\n",
      "Red flags: 10\n",
      "Orange flags: 19\n",
      "Yellow flags: 23\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.8s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=500; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=60, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=800; total time=   0.8s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.6s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=70, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=600; total time=   0.7s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=1, min_samples_split=7, n_estimators=800; total time=   0.9s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=5, n_estimators=500; total time=   0.5s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=2, min_samples_split=7, n_estimators=400; total time=   0.4s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=3, n_estimators=600; total time=   0.6s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=5, n_estimators=100; total time=   0.1s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=300; total time=   0.3s\n",
      "[CV] END bootstrap=False, max_depth=80, max_features=sqrt, min_samples_leaf=3, min_samples_split=7, n_estimators=800; total time=   0.6s\n"
     ]
    }
   ],
   "source": [
    "risk_probas = []\n",
    "# Probability >= 95%\n",
    "black_flags = []\n",
    "# Probability > 85% and < 95%\n",
    "red_flags = []\n",
    "# Probability > 70% and < 85%\n",
    "orange_flags = []\n",
    "#Probability > 50% and < 70%\n",
    "yellow_flags = []\n",
    "\n",
    "for i in best_model_predictions_proba:\n",
    "    if i[1] > [0]:\n",
    "        risk_probas.append(i[1])\n",
    "        \n",
    "for i in risk_probas:\n",
    "    if i >= 0.95:\n",
    "        black_flags.append(i)\n",
    "    elif i >= 0.85:\n",
    "        red_flags.append(i)\n",
    "    elif i >= 0.75:\n",
    "        orange_flags.append(i)\n",
    "    else:\n",
    "        yellow_flags.append(i)\n",
    "        \n",
    "print (\"Black flags: \" + str(len(black_flags)))\n",
    "print (\"Red flags: \" + str(len(red_flags)))\n",
    "print (\"Orange flags: \" + str(len(orange_flags)))\n",
    "print (\"Yellow flags: \" + str(len(yellow_flags)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b37f2b8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Printing model metrics\n",
    "print(confusion_matrix(y_test,predictions))  \n",
    "print(classification_report(y_test,predictions))  \n",
    "print(accuracy_score(y_test, predictions))\n",
    "\n",
    "# Printing best model metrics\n",
    "best_grid_predictions = best_grid.predict(X_test)\n",
    "\n",
    "print(confusion_matrix(y_test,best_grid_predictions))  \n",
    "print(classification_report(y_test,best_grid_predictions))  \n",
    "print(accuracy_score(y_test, best_grid_predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "517116b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature importances\n",
    "\n",
    "featureImp = pd.Series(text_classifier.feature_importances_, tfidfconverter.get_feature_names()).sort_values(ascending=False)\n",
    "print(featureImp.head(50))\n",
    "\n",
    "featureImp = pd.Series(best_random.feature_importances_,index=tfidfconverter.get_feature_names()).sort_values(ascending=False)\n",
    "print(featureImp.head(50))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbfa6908",
   "metadata": {},
   "outputs": [],
   "source": [
    "app = Flask(__name__)\n",
    "@app.route('/classify', methods=['POST'])\n",
    "def classifyText():\n",
    "    text = request.json['text']\n",
    "    vect_message = tfidfconverter.transform([text])\n",
    "\n",
    "    classification = best_grid.predict(vect_message)[0]\n",
    "    classification_proba = best_grid.predict_proba(vect_message)[0]\n",
    "    probability = classification_proba[0] if (classification_proba[0] > classification_proba[1]) else classification_proba[1]\n",
    "    \n",
    "    response = classification + \": \" + str(probability)\n",
    "    print (text + \": \" + response)\n",
    "    return response\n",
    "\n",
    "if __name__==\"__main__\":\n",
    "    app.run()"
   ]
  }
 ],
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