lgb_pr_demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "import lightgbm as gbm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read dataset\n",
    "\n",
    "data = pd.read_csv(\"dataset/diabetes.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
       "0            6      148             72             35        0  33.6   \n",
       "1            1       85             66             29        0  26.6   \n",
       "2            8      183             64              0        0  23.3   \n",
       "3            1       89             66             23       94  28.1   \n",
       "4            0      137             40             35      168  43.1   \n",
       "\n",
       "   DiabetesPedigreeFunction  Age  Outcome  \n",
       "0                     0.627   50        1  \n",
       "1                     0.351   31        0  \n",
       "2                     0.672   32        1  \n",
       "3                     0.167   21        0  \n",
       "4                     2.288   33        1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "trn_x, val_x, trn_y, val_y = train_test_split(data.drop('Outcome',axis=1).values,data.Outcome.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's binary_logloss: 0.630662\n",
      "[2]\tvalid_0's binary_logloss: 0.607073\n",
      "[3]\tvalid_0's binary_logloss: 0.590443\n",
      "[4]\tvalid_0's binary_logloss: 0.576605\n",
      "[5]\tvalid_0's binary_logloss: 0.559809\n",
      "[6]\tvalid_0's binary_logloss: 0.547444\n",
      "[7]\tvalid_0's binary_logloss: 0.540092\n",
      "[8]\tvalid_0's binary_logloss: 0.531976\n",
      "[9]\tvalid_0's binary_logloss: 0.525383\n",
      "[10]\tvalid_0's binary_logloss: 0.52185\n",
      "[11]\tvalid_0's binary_logloss: 0.518055\n",
      "[12]\tvalid_0's binary_logloss: 0.514917\n",
      "[13]\tvalid_0's binary_logloss: 0.513998\n",
      "[14]\tvalid_0's binary_logloss: 0.513019\n",
      "[15]\tvalid_0's binary_logloss: 0.510348\n",
      "[16]\tvalid_0's binary_logloss: 0.505902\n",
      "[17]\tvalid_0's binary_logloss: 0.507434\n",
      "[18]\tvalid_0's binary_logloss: 0.507881\n",
      "[19]\tvalid_0's binary_logloss: 0.507921\n",
      "[20]\tvalid_0's binary_logloss: 0.510691\n",
      "[21]\tvalid_0's binary_logloss: 0.509762\n",
      "[22]\tvalid_0's binary_logloss: 0.51007\n",
      "[23]\tvalid_0's binary_logloss: 0.511956\n",
      "[24]\tvalid_0's binary_logloss: 0.511897\n",
      "[25]\tvalid_0's binary_logloss: 0.511366\n",
      "[26]\tvalid_0's binary_logloss: 0.514794\n",
      "[27]\tvalid_0's binary_logloss: 0.516962\n",
      "[28]\tvalid_0's binary_logloss: 0.519404\n",
      "[29]\tvalid_0's binary_logloss: 0.521698\n",
      "[30]\tvalid_0's binary_logloss: 0.526811\n",
      "[31]\tvalid_0's binary_logloss: 0.527959\n",
      "[32]\tvalid_0's binary_logloss: 0.533546\n",
      "[33]\tvalid_0's binary_logloss: 0.535601\n",
      "[34]\tvalid_0's binary_logloss: 0.543296\n",
      "[35]\tvalid_0's binary_logloss: 0.547725\n",
      "[36]\tvalid_0's binary_logloss: 0.549107\n",
      "[37]\tvalid_0's binary_logloss: 0.551053\n",
      "[38]\tvalid_0's binary_logloss: 0.553008\n",
      "[39]\tvalid_0's binary_logloss: 0.557354\n",
      "[40]\tvalid_0's binary_logloss: 0.5596\n",
      "[41]\tvalid_0's binary_logloss: 0.562226\n",
      "[42]\tvalid_0's binary_logloss: 0.564139\n",
      "[43]\tvalid_0's binary_logloss: 0.566118\n",
      "[44]\tvalid_0's binary_logloss: 0.568323\n",
      "[45]\tvalid_0's binary_logloss: 0.572432\n",
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      "[47]\tvalid_0's binary_logloss: 0.580474\n",
      "[48]\tvalid_0's binary_logloss: 0.585275\n",
      "[49]\tvalid_0's binary_logloss: 0.589967\n",
      "[50]\tvalid_0's binary_logloss: 0.587958\n",
      "[51]\tvalid_0's binary_logloss: 0.593394\n",
      "[52]\tvalid_0's binary_logloss: 0.599699\n",
      "[53]\tvalid_0's binary_logloss: 0.598983\n",
      "[54]\tvalid_0's binary_logloss: 0.602924\n",
      "[55]\tvalid_0's binary_logloss: 0.606248\n",
      "[56]\tvalid_0's binary_logloss: 0.61188\n",
      "[57]\tvalid_0's binary_logloss: 0.614042\n",
      "[58]\tvalid_0's binary_logloss: 0.617693\n",
      "[59]\tvalid_0's binary_logloss: 0.618897\n",
      "[60]\tvalid_0's binary_logloss: 0.618905\n",
      "[61]\tvalid_0's binary_logloss: 0.621496\n",
      "[62]\tvalid_0's binary_logloss: 0.624615\n",
      "[63]\tvalid_0's binary_logloss: 0.624323\n",
      "[64]\tvalid_0's binary_logloss: 0.625369\n",
      "[65]\tvalid_0's binary_logloss: 0.630699\n",
      "[66]\tvalid_0's binary_logloss: 0.635063\n",
      "[67]\tvalid_0's binary_logloss: 0.638891\n",
      "[68]\tvalid_0's binary_logloss: 0.642304\n",
      "[69]\tvalid_0's binary_logloss: 0.644197\n",
      "[70]\tvalid_0's binary_logloss: 0.64731\n",
      "[71]\tvalid_0's binary_logloss: 0.650049\n",
      "[72]\tvalid_0's binary_logloss: 0.653526\n",
      "[73]\tvalid_0's binary_logloss: 0.654002\n",
      "[74]\tvalid_0's binary_logloss: 0.65723\n",
      "[75]\tvalid_0's binary_logloss: 0.662672\n",
      "[76]\tvalid_0's binary_logloss: 0.667324\n",
      "[77]\tvalid_0's binary_logloss: 0.669028\n",
      "[78]\tvalid_0's binary_logloss: 0.670085\n",
      "[79]\tvalid_0's binary_logloss: 0.671855\n",
      "[80]\tvalid_0's binary_logloss: 0.673094\n",
      "[81]\tvalid_0's binary_logloss: 0.679517\n",
      "[82]\tvalid_0's binary_logloss: 0.683549\n",
      "[83]\tvalid_0's binary_logloss: 0.686472\n",
      "[84]\tvalid_0's binary_logloss: 0.689026\n",
      "[85]\tvalid_0's binary_logloss: 0.693684\n",
      "[86]\tvalid_0's binary_logloss: 0.696142\n",
      "[87]\tvalid_0's binary_logloss: 0.70197\n",
      "[88]\tvalid_0's binary_logloss: 0.705491\n",
      "[89]\tvalid_0's binary_logloss: 0.706769\n",
      "[90]\tvalid_0's binary_logloss: 0.710832\n",
      "[91]\tvalid_0's binary_logloss: 0.713006\n",
      "[92]\tvalid_0's binary_logloss: 0.717662\n",
      "[93]\tvalid_0's binary_logloss: 0.717796\n",
      "[94]\tvalid_0's binary_logloss: 0.720188\n",
      "[95]\tvalid_0's binary_logloss: 0.723047\n",
      "[96]\tvalid_0's binary_logloss: 0.725802\n",
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      "[99]\tvalid_0's binary_logloss: 0.732778\n",
      "[100]\tvalid_0's binary_logloss: 0.736156\n"
     ]
    }
   ],
   "source": [
    "trn_dataset = gbm.Dataset(trn_x,trn_y)\n",
    "val_dataset = gbm.Dataset(val_x,val_y)\n",
    "\n",
    "parameters = {\n",
    "    \"objective\": \"binary\",\n",
    "    \n",
    "}\n",
    "\n",
    "clf = gbm.train(parameters,trn_dataset,valid_sets=val_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7239583333333334"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "rounder = lambda x: 1 if x > 0.51 else 0\n",
    "\n",
    "predicted = []\n",
    "\n",
    "for p in clf.predict(val_x):\n",
    "    predicted.append(rounder(p))\n",
    "    \n",
    "accuracy_score(val_y, predicted)   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5e942abe90>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cGRGRLm8i6fkQEZsk5Z/Phrzlauo/1/eAj0iubwE8AAzfVoCtWzZnUXrB0urK5XL1/mGa22dr9oS2effdd2nZsiVt27Zl3bp1PP7444wePZrTTz+dWbNmccEFFzB79myOOOIIAE477TRGjBhBVVUVGzduZO7cuVxxxRUZn8XOV8xkNAu4UdJFEXEXgKRjgdXAOZKmkEwUGACMpG7CqQAuTScTdAL6FSvIiAhJD5PMpJsFfAF4uVjHM7M924oVKzjvvPOorq5m06ZNnH322QwePJj+/fszZMgQfvKTn1BSUsLdd98NQPfu3TnppJPo06cPzZo148ILL6RXr50+qThzRUtG6Yf8GcBESVcB60mndgMlwAIggFERsTKd2l1jDrCUZBjuJeD5YsWZGg38WtJE4F3g/CIfz8z2UH369OGFF17Yorxt27Y88kjhaesjR45k5MiRxQ5tl1bUwdmIeAs4u8Cqkekrv24FyaQH0mG4IfXssyRveUyhdRExGZicVz54G3EuI+mhmZlZBnwHBjMzy9zuOW1lB0maC7TarHhoRJRnEY+ZmSWaVDKKiOOyjsHMzLbkYTozM8uck5GZmWXOycjMzDLnZGRmZplzMjIzs8w5GZmZWeacjMzMLHNORmZmljknIzMzy5yTkZmZZc7JyMzMMudkZGa2HdavX0+/fv3o27cvPXv25Ac/+AEAw4YN47Of/SylpaWUlpYyf/58IHl67f77719bfv3112cZ/i6rSd0otTGtq6ym61WFH5TV1F3Zu4phbpt6uX3qtyu3TcXNpwDQqlUrZs2aRUlJCZWVlfTv359BgwYBMG7cOM4666wttv3c5z7HjBkzdmq8u5ui9owkHSTpd5Jek/SypD9LOqKeul0lvVTMeOoj6UeSlktak8XxzWz3IYmSkuQZn5WVlVRWViIp46h2f0VLRkr+60wDchFxaET0AK4GOhbrmJ/Aw0C/rIMws91DdXU1paWldOjQgYEDB3LcccnTaa655hr69OnDFVdcwYYNG2rr//3vf6dv374MGjSIhQsXZhX2Lk3JE76LsGPp88CYiBiwWbmAscAgIIAbIuJ+SV2BGRHRS9Iw4JiIGJFuMwMYHxG5tPdyO/BFYDVJghsLdAEuj4jp6fanAvsAhwLTImJUA2Jek/9Y8wLrLwYuBmjf/sCjr514V0Obo0np2BreXpd1FLsut0/9duW26d1p/y3K1qxZw/e//33+8z//k/3224927dpRWVnJhAkT+PSnP815553H2rVradasGa1bt+bpp5/mtttu4ze/+c12H3/NmjW1PbLd2YknnjgvIo7ZvLyY14x6AfMKlJ8JlAJ9gfbAs5Ke3I79tiHpbY2WNA24ARgI9ACmANPTeqXAUcAGYJGkWyNi+Q6dSSoi7gTuBOjS7bCYUO5LboVc2bsKt0393D7125XbpmJIWcHyefPm8d5773H++efXlu21116MHz+esrK625SVlTFp0iR69epF+/btt+v4uVxui/3tSbL4r94fmBoR1cDbkmYDxwIvNnD7jcDMdLkc2BARlZLKga559Z6IiA8AJL0MHAJ8omSUr3XL5ixKL2haXblcrt4/XHP7bM3u0DbvvvsuLVu2pG3btqxbt47HH3+c0aNHs2LFCg4++GAigj/+8Y/06tULgJUrV9KxY0ck8cwzz7Bp0yYOOOCAjM9i11PMZLQQ2HJaCTTkSl8Vda9n7Z23XBkfjy1uIun5EBGbJOWfz4a85Wo8c9DMGsGKFSs477zzqK6uZtOmTZx99tkMHjyYz3/+87z77rtEBKWlpUyaNAmABx98kDvuuIMWLVrQunVrfve733nCQwHF/ICeBdwo6aKIuAtA0rEk13nOkTQFaAcMAEZSN+FUAJdKagZ0wpMLzGwX0adPH1544YUtymfNmlWw/ogRIxgxYkSxw9rtFW02Xdp7OQMYmE7tXgiMAe4jGZJbQJKwRkXEys02nwMsJRmGGw88X6w4ASSNlfQGsI+kNySNKebxzMysrqIOXUXEW8DZBVaNTF/5dStIJj3UJLIh9eyzJG95TKF1ETEZmJxXPngbcY4CtjnbzszMisO3AzIzs8w1qYv6kuYCrTYrHhoR5VnEY2ZmiSaVjCLiuKxjMDOzLXmYzszMMudkZGZmmXMyMjOzzDkZmZlZ5pyMzMwsc05GZmaWOScjMzPL3HYnI0mfktSnGMGYmVnT1KBkJCknaT9J7UhucPorSbcUNzQzM2sqGtoz2j8i/o/kKa2/ioijSR77bWZm9ok1NBm1kHQwyR24ZxQxHjOzLaxfv55+/frRt29fevbsyQ9+8AMAli5dynHHHcfhhx/OOeecw8aNG2u3+f3vf0+PHj3o2bMnX//617MK3RqoocnoeuBR4LWIeFZSN2BJ8cIyM/tYq1atmDVrFgsWLGD+/PnMnDmTp59+mtGjR3PFFVewZMkSPvWpT/HLX/4SgCVLlnDTTTcxZ84cFi5cyMSJEzM+A9sWffwE7yLsXDoImAgcS/IY8Arg8ohYXKBuV2BGRPQqWkAFSNoX+GteUWfgNxFx+da269LtsGh29k+LGtvu6sreVUwob1L34N0ubp/6bd42FTefskWdjz76iP79+3PHHXdwyimnsHLlSlq0aMHf//53xowZw6OPPsqoUaM44ogjuPDCC3dm+EWVy+UoKyvLOoxPTNK8iDhm8/KGTmA4QtITkl5K3/eR9L1tbCNgGpCLiEMjogdwNdBx+8Mvnoj4MCJKa17AMuAPWcdlZnVVV1dTWlpKhw4dGDhwIIceeiht27alRYskeXXu3Jk333wTgMWLF7N48WL+9V//leOPP56ZM2dmGbo1QEO/nt1F8mTWXwBExIuS7gNu2Mo2JwKVETGppiAi5isxDhgEBHBDRNyfv6GkYcAxETEifT8DGB8ROUlrgNtJJlCsJklwY4EuJL2u6en2pwL7AIcC09KnuW6VpMOBDtTtKeWvvxi4GKB9+wO5tnfVtnbZJHVsnXzDtcLcPvXbvG1yuVyd9RMnTmTNmjV8//vfp1OnTqxbt662zjvvvMNHH31ELpfj7bff5r333uO6667j3XffZejQofzqV7+ipKSE3dWaNWu2aI89SUOT0T4R8UzS2am1rb+mXsC8AuVnAqVAX6A98KykJxsYB0Abkt7WaEnTSBLiQKAHMAWYntYrBY4iGR5cJOnWiFi+jX2fC9wf9YxdRsSdwJ2QDNN5qKUwD0NtndunflsM0w0pK1hv3rx5bNiwgQ0bNtC/f//aYbrDDz+csrIy+vbty/HHH88Xv5hM+r377rvp2LEjxx577M44jaLYU4bp6tPQv4hVkg4l6ckg6SxgxQ4esz8wNSKqgbclzSa5pvRiA7ffCNT0ucuBDRFRKakc6JpX74mI+CCN92XgEGBbyehrwNCGBNG6ZXMWFRjPtuSPpr4PEXP7bE19bfPuu+/SsmVL2rZty7p163j88ccZPXo0J554Ig8++CBf+9rXmDJlCqeddhoAp59+OlOnTmXYsGGsWrWKxYsX061bt518NrY9GpqMLiPpERwp6U1gKTBkG9ssBM4qUK4CZZurou71rL3zlivzei6bSHo+RMQmSfnnsyFvuZptnKukvkCLiCjUmzOzDK1YsYLzzjuP6upqNm3axNlnn83gwYPp0aMHX/va1/je977HUUcdxfDhwwH48pe/zF/+8hd69OhB8+bNGTduHAcccEDGZ2Fbs81kJKkZyfWbL0pqAzSLiA8bsO9ZwI2SLoqIu9J9HUtyneccSVOAdsAAkutR+QmnArg0PXYnoN92nNOOOheYuhOOY2bbqU+fPrzwwgtblHfr1o1nnnlmi3JJ3HLLLdxyi28Us7vYZjJKexwjgN9HxNqG7jgiQtIZwERJVwHrSad2AyUktxUKYFRErEyndteYQ9L7KgdeAp5v6HE/gbOBk3fCcczMbDMNHaZ7TNJ3gfuB2oQUEf+7tY0i4i2SD/nNjUxf+XUrSCY9kA7DFRwGjIiSvOUxhdZFxGRgcl754K3FmdbxgLKZWUYamowuSP+9LK8sAH+Am5nZJ9agZBQRny12IDuDpLlAq82Kh0ZEeRbxmJlZokHJSNI3CpVHxL2NG05xRcRxWcdgZmZbaugwXf4vxfYGvkAyqWC3SkZmZrZraugw3bfy30vaH/h1USIyM7MmZ7sfO576CDi8MQMxM7Omq6HXjB4mvRUQSQLrATxQrKDMzKxpaeg1o/F5y1XAsoh4owjxmJlZE9TQYbqTI2J2+poTEW9I+nFRIzMzsyajocloYIGyQY0ZiJmZNV3bupP1fwCXAt0k5T/iYV+S+8eZmZl9Ytu6ZnQf8F/ATcBVeeUfbuu+dGZmZg211WSUPpzuA5LHKyCpA8mPXksklUTE/xQ/RDMz29M16JqRpK9IWkLyWIfZJI+C+K8ixmVmRbJ8+XJOPPFEunfvTs+ePfnpT39aZ/348eORxKpVq+qUP/vsszRv3pwHH3xwZ4ZrTURDJzDcABwPLE5vmvoFfM3IbLfUokULJkyYwCuvvMLTTz/N7bffzssvvwwkieqxxx6jS5cudbaprq5m9OjRfPnLX84iZGsCGvo7o8qIeE9SM0nNIuK/GzK1W9JBwESSe9ttIH24XkQsLlC3KzAjIno1NPjGIGkfkh/wHkryePKHI+KqrW8F6yqr6XrVI8UOb7d0Ze8qhrlt6pVl+1TcfAoHH3wwBx98MAD77rsv3bt3580336RHjx5cccUVjB07ltNOO63Odrfeeitf/epXefbZZ7MI25qAhvaM3pdUAvwV+K2kn5L8+LVekgRMA3IRcWhE9ACuBjp+koCLZHxEHAkcBfyrJE9btyahoqKCF154geOOO47p06fTqVMn+vbtW6fOm2++ybRp07jkkksyitKagob2jE4D1pE8MnwIsD9w/Ta2OZGkRzWppiAi5isxjuR3SgHcEBH3528oaRhwTESMSN/PIEkYOUlrgNuBLwKrSRLcWKALSa9rerr9qcA+JD2eaRExqlCQEfER8N/p8kZJzwOdC9WVdDFwMUD79gdybe+t5uMmq2Pr5Nu/FZZl++RyudrldevW8e1vf5sLL7yQv/3tb4wePZpx48aRy+VYv349c+bMYf/992fMmDGcc845/PWvf2XlypUsXLiQ9u3bFyW+NWvW1InRPrant01D79q9VtIhwOERMSUd2mq+jc16AfMKlJ8JlAJ9gfbAs5Ke3I6Y25D0tkZLmkZyPWsgyf3ypgDT03qlJD2dDcAiSbdGxPKt7VhSW+ArwE8LrY+IO4E7Abp0OywmlDc0lzctV/auwm1Tvyzbp2JIGQCVlZUMHjyYSy65hO985zuUl5fz3nvvMWLECABWrVrFt771LZ555hmWLVvG2LFja8uff/55+vbty+mnn97o8eVyOcrKyhp9v3uCPb1tGnqj1ItIegTtSHoanYBJJBMZtld/YGpEVANvS5pNck3pxa1vVmsjMDNdLgc2RESlpHKga169J9Kp6Uh6GTgEqDcZSWoBTAV+FhGvb8f5mO1WIoLhw4fTvXt3vvOd7wDQu3dv3nnnndo6Xbt25bnnnqN9+/YsXbq0tnzYsGEMHjy4KInImraGfj27DOgHzAWIiCXpb462ZiFwVoFyNeB4VdS9nrV33nJlRNTcQXwTSc+HiNiUJpQaG/KWq9n2ud4JLImIiQ2Ij9Ytm7Po5lMaUrXJyeVytd/AbUtZt8+cOXP49a9/Te/evSktLQXgxhtv5OSTT84sJrOGJqMN6fUUoLYXEVvfhFnAjZIuioi70u2OJbnOc46kKSQ9rQHASOomnArgUknNSHph/RoY5w6RdAPJdbALi3kcs11B//79+fj7XGEVFRUFyydPntz4AZnR8GQ0W9LVQGtJA0nuV/fw1jaIiJB0BjBR0lXAetKp3UAJsIAkoY2KiJXp1O4ac0h+YFsOvETyiPOikNQZuAZ4FXg+Tbi3RcTdxTqmmZnV1dBkdBUwnCQ5fBP4M7DND+uIeAs4u8Cqkekrv24FyaQH0mG4IfXssyRveUyhdRExGZicVz54KzG+QcOGDs3MrEi2ddfuLhHxPxGxCbgrfZmZmTWqbf3o9Y81C5IeKnIsRSdprqT5m716Zx2XmXKRM2sAABUVSURBVFlTt61huvzhq27FDGRniIjjso7BzMy2tK2eUdSzbGZm1mi21TPqK+n/SHpIrdNl0vcREfsVNTozM2sStvVwvW3d8sfMzOwTa+hdu83MzIrGycjMzDLnZGRmZplzMjIzs8w5GZmZWeacjMzMLHNORmZmljknI2tyLrjgAjp06ECvXr1qy8aMGUOnTp0oLS2ltLSUP//5zwA888wztWV9+/Zl2rRpWYVttkdzMrImZ9iwYcycOXOL8iuuuIL58+czf/782qee9urVi+eee4758+czc+ZMvvnNb1JVVbWzQzbb4zX0eUY7RNJBwETgWJLHgFcAl0fE4gJ1uwIzIqLX5uuKTdJM4GCS9vgrcFlEVG9tm3WV1XS96pGdEd5u58reVQzbBdumIn1M/IABA+p9kunm9tlnn9rl9evXU/O0YzNrXEXrGSn5q50G5CLi0IjoAVwNdCzWMT+BsyOiL8nD/Q4E/i3jeCwDt912G3369OGCCy5g9erVteVz586lZ8+e9O7dm0mTJtGiRVG/w5k1ScX8qzoRqIyISTUFETFfiXHAIJI7gd8QEffnbyhpGHBMRIxI388AxkdETtIa4Hbgi8BqkgQ3FuhC0uuanm5/KrAPcCgwLSJG1RdoRNTcALYFsBf13KFc0sXAxQDt2x/Itb09XFNIx9ZJ72hXk8vlapdXrlzJ2rVra8v69OnDL3/5SyRxzz338PWvf53Ro0fX1r/99ttZtmwZV199NW3atGGvvfba4TjWrFlTJxb7mNumfnt62xQzGfUC5hUoPxMoBfoC7YFnJT25HfttQ9LbGi1pGnADMBDoAUwBpqf1SoGjSIYHF0m6NSKW17dTSY8C/YD/Ah4sVCci7gTuBOjS7bCYUO5vyIVc2buKXbFtKoaUfbxcUUGbNm0oKyvbol63bt0YPHhwwXWTJ0+mXbt2HHPMMTscRy6XK7hvc9tszZ7eNllMYOgPTI2I6oh4G5hNck2poTYCNVefy4HZEVGZLnfNq/dERHwQEeuBl4FDtrbTiPgyyXWjVsDntyMe2wOsWLGidnnatGm1M+2WLl1aO2Fh2bJlLFq0iK5du2YRotkerZhfXxcCZxUob8gV4CrqJsq985YrI6JmGG0TSc+HiNgkKf98NuQtV9OAc42I9ZKmA6cBj22tbuuWzVmUXhC3unK5XJ1eyK7m3HPPJZfLsWrVKjp37sx1111HLpdj/vz5SKJr16784he/AOCpp57i5ptvpmXLljRr1oyf//zntG/fPuMzMNvzFDMZzQJulHRRRNwFIOlYkus850iaArQDBgAjqZtwKoBLJTUDOpEMnxWFpBJg34hYkSazk0lm1NkeaurUqVuUDR8+vGDdoUOHMnTo0GKHZNbkFS0ZRURIOgOYKOkqYD3p1G6gBFhAMlFgVESsTKd215gDLCUZensJeL5YcZJcg5ouqRXQnCSJTtr6JmZm1piKepU5It4Czi6wamT6yq9bQTLpgXQYbkg9+yzJWx5TaF1ETAYm55UP3kqMb7N916zMzKyR+Q4MZmaWuV1v/m0RSZpLMlsu39CIKM8iHjMzSzSpZBQRx2Udg5mZbcnDdGZmljknIzMzy5yTkZmZZc7JyMzMMudkZGZmmXMyMjOzzDkZmZlZ5pyMzMwsc05GZmaWOScjMzPLnJOR7ZEuuOACOnToUPvE1nzjx49HEqtWrQLgT3/6E3369KG0tJRjjjmGp556ameHa9bkORnZHmnYsGHMnDlzi/Lly5fz2GOP0aVLl9qyL3zhCyxYsID58+dzzz33cOGFF+7MUM2MIt8oVdJBwESS5wVtIH24XkQsLlC3KzAjIrb8KruTpI8c79aQGNZVVtP1qkd2QlS7nyt7VzEso7apSB8FP2DAACoqKrZYf8UVVzB27FhOO+202rKSktpHZLF27VokFT1OM6uraD0jJX/R04BcRBwaET2Aq4GOxTrmJyHpTGBN1nFY8UyfPp1OnTrRt2/fLdZNmzaNI488klNOOYV77rkng+jMmrZi9oxOBCojovYR3hExX4lxwCCSx47fEBH3528oaRhwTESMSN/PAMZHRE7SGuB24IvAapIENxboQtLrmp5ufyqwD3AoMC0iRtUXqKQS4DvAxcDvt1Lv4rQO7dsfyLW9q7ajOZqOjq2T3lEWcrlc7fLKlStZu3YtuVyO9evXM3r0aMaNG1f7fs6cOey///4AfOpTn2LSpEksWLCAESNGMGHChKLFuGbNmjpx2sfcNvXb09ummMmoFzCvQPmZQCnQF2gPPCvpye3YbxuS3tZoSdOAG4CBQA9gCjA9rVcKHEUyPLhI0q0Rsbyeff4QmAB8tLUDR8SdwJ0AXbodFhPKm9TjoBrsyt5VZNU2FUPKPl6uqKBNmzaUlZVRXl7Oe++9x4gRIwBYtWoV3/rWt3jmmWc46KCDarcpKytj4sSJ9OrVi/bt2xclxlwuR1lZ2TbrNUVum/rt6W2TxQSG/sDUiKiOiLeB2STXlBpqI1BzZbocmB0Rlely17x6T0TEBxGxHngZOKTQziSVAodFxLTtOw3bnfTu3Zt33nmHiooKKioq6Ny5M88//zwHHXQQ//jHP4gIAJ5//nk2btzIAQcckHHEZk1LMb++LgTOKlDekKvDVdRNlHvnLVdGzScHbCLp+RARmyTln8+GvOVq6j/XfwGOllSR1ukgKRcRZVsLsHXL5ixKL5ZbXblcrk4PJQvnnnsuuVyOVatW0blzZ6677jqGDx9esO5DDz3EvffeS8uWLWndujX333+/JzGY7WTFTEazgBslXRQRdwFIOpbkOs85kqYA7YABwEjqJpwK4FJJzYBOQL9iBRkRdwB3pPF1JZnRV1as49nOMXXq1K2uz59pN3r0aEaPHl3kiMxsa4qWjCIiJJ0BTJR0FbCedGo3UAIsIJnAMCoiVqaJoMYcYCnJ0NtLwPPFitPMzLJX1KvMEfEWcHaBVSPTV37dCpJJD6TDcEPq2WdJ3vKYQusiYjIwOa98cAPjrY3BzMx2Ht+BwczMMtek5iZLmgu02qx4aESUZxGPmZklmlQyiojjso7BzMy25GE6MzPLnJORmZllzsnIzMwy52RkZmaZczIyM7PMORmZmVnmnIzMzCxzTkZmZpY5JyMzM8uck5GZmWXOych2GxdccAEdOnSgV6+Pb6w+cuRIjjzySPr06cMZZ5zB+++/D0BlZSXnnXcevXv3pnv37tx0001ZhW1mDeBkZLuNYcOGMXPmzDplAwcO5KWXXuLFF1/kiCOOqE06DzzwABs2bKC8vJx58+bxi1/8os4D9cxs11LUG6VKOgiYCBxL8hjwCuDyiFhcoG5Xkqes7vTnCUk6muT5R62BPwPfznu0eUHrKqvpetUjOyG63c+VvasY1ohtU5E+3n3AgAFbJJQvfelLtcvHH388Dz74IACSWLt2LVVVVaxbt4699tqL/fbbr9FiMrPGVbSekSQB04BcRBwaET2Aq4GOxTrmJ3AHcDFwePo6KdtwbEfcc889DBo0CICzzjqLNm3acPDBB9OlSxe++93v0q5du4wjNLP6FHOY7kSgMiIm1RRExHzgKUnjJL0kqVzSOZtvKGmYpNvy3s+QVJYur5H0Y0nzJD0uqZ+knKTXJZ2at/0fJM2UtETS2PqClHQwsF9E/D3tDd0LnN5YjWA7x49+9CNatGjBkCHJA4KfeeYZmjdvzltvvcXSpUuZMGECr7/+esZRmll9ijlM1wuYV6D8TKAU6Au0B56V9OR27LcNSW9rtKRpwA3AQKAHMAWYntYrBY4iGR5cJOnWiFheYH+dgDfy3r+Rlm1B0sUkPSjatz+Qa3tXbUfYTUfH1slQXWPJ5XK1yytXrmTt2rV1ymbOnMnDDz/MhAkTmD17NgATJ06kR48ezJkzB4Bu3boxZcoUTjzxxEaLa0etWbOmTvz2MbdN/fb0tsni4Xr9gakRUQ28LWk2yTWlFxu4/Uag5ip2ObAhIiollQNd8+o9EREfAEh6GTgEKJSMVKCs4PWiiLgTuBOgS7fDYkJ5k3o2YYNd2buKxmybiiFlHy9XVNCmTRvKypKymTNnMn36dGbPns2BBx5YW2/u3Lm8+uqrnHDCCXz00UcsW7aMH//4x/Tp06fR4tpRuVyuNn6ry21Tvz29bYr5aboQOKtAeaEP/81VUXcIce+85cq8yQWbSHo+RMQmSfnnsyFvuZr6z/UNoHPe+87AW9sKsHXL5ixKL6xbXblcrk4CaSznnnsuuVyOVatW0blzZ6677jpuuukmNmzYwMCBA4FkEsOkSZO47LLLOP/88+nVqxcRwfnnn79LJCIzK6yYyWgWcKOkiyLiLgBJxwKrgXMkTQHaAQOAkdRNOBXApZKakQyZ9StWkBGxQtKHko4H5gLfAG4t1vFsx02dOnWLsuHDhxesW1JSwgMPPFDskMyskRQtGUVESDoDmCjpKmA96dRuoARYQDIcNioiVqZTu2vMAZaSDMO9BDxfrDhT/8HHU7v/K32ZmdlOUtSLHhHxFnB2gVUj01d+3QqSSQ+kw3BD6tlnSd7ymELrImIySXKpKR+8jTifqzm2mZntfL4Dg5mZZa5JTQeTNBdotVnx0IgozyIeMzNLNKlkFBHHZR2DmZltycN0ZmaWOScjMzPLnJORmZllzsnIzMwy52RkZmaZczIyM7PMORmZmVnmnIzMzCxzTkZmZpY5JyMzM8uck5GZmWXOycjMzDLnZGRmZplzMjIzs8w5GZmZWeaUPOHbtpekD4FFWcexi2oPrMo6iF2Y26d+bpv67Sltc0hEHLh5YZN6uF4jWxQRx2QdxK5I0nNum/q5ferntqnfnt42HqYzM7PMORmZmVnmnIx23J1ZB7ALc9tsndunfm6b+u3RbeMJDGZmljn3jMzMLHNORmZmljkno+0k6SRJiyT9Q9JVWceTBUn3SHpH0kt5Ze0kPSZpSfrvp9JySfpZ2l4vSvrn7CIvPkmfkfTfkl6RtFDSt9PyJt8+kvaW9IykBWnbXJeWf1bS3LRt7pe0V1reKn3/j3R91yzj31kkNZf0gqQZ6fsm0T5ORttBUnPgdmAQ0AM4V1KPbKPKxGTgpM3KrgKeiIjDgSfS95C01eHp62Lgjp0UY1aqgCsjojtwPHBZ+v+I2wc2AJ+PiL5AKXCSpOOBHwM/SdtmNTA8rT8cWB0RhwE/Ses1Bd8GXsl73yTax8lo+/QD/hERr0fERuB3wGkZx7TTRcSTwP9uVnwaMCVdngKcnld+bySeBtpKOnjnRLrzRcSKiHg+Xf6Q5EOlE24f0nNck75tmb4C+DzwYFq+edvUtNmDwBckaSeFmwlJnYFTgLvT96KJtI+T0fbpBCzPe/9GWmbQMSJWQPKBDHRIy5tsm6XDJkcBc3H7ALVDUPOBd4DHgNeA9yOiKq2Sf/61bZOu/wA4YOdGvNNNBEYBm9L3B9BE2sfJaPsU+tbhufFb1yTbTFIJ8BBweUT839aqFijbY9snIqojohToTDLS0L1QtfTfJtU2kgYD70TEvPziAlX3yPZxMto+bwCfyXvfGXgro1h2NW/XDC+l/76Tlje5NpPUkiQR/TYi/pAWu33yRMT7QI7kulpbSTX3ycw//9q2Sdfvz5bDw3uSfwVOlVRBcgng8yQ9pSbRPk5G2+dZ4PB0dstewNeA6RnHtKuYDpyXLp8H/Cmv/BvprLHjgQ9qhqv2ROmY/S+BVyLilrxVTb59JB0oqW263Br4Isk1tf8Gzkqrbd42NW12FjAr9uBf6UfE/x8RnSOiK8lny6yIGEJTaZ+I8Gs7XsDJwGKSse5rso4nozaYCqwAKkm+nQ0nGat+AliS/tsurSuSGYivAeXAMVnHX+S26U8yVPIiMD99nez2CYA+wAtp27wEXJuWdwOeAf4BPAC0Ssv3Tt//I13fLetz2IltVQbMaErt49sBmZlZ5jxMZ2ZmmXMyMjOzzDkZmZlZ5pyMzMwsc05GZmaWOScjs81IqpY0P+/VdQf20VbSpY0fXe3+T93Zd42XdHoTvTGw7QSe2m22GUlrIqLkE+6jK8nvRHpt53bNI6L6kxy7GNJf+N9Nck4Pbqu+2fZyz8isAdIbfI6T9Gz63KFvpuUlkp6Q9Lykckk1d3G/GTg07VmNk1RW83yadLvbJA1LlyskXSvpKeDfJB0qaaakeZL+KunIAvEMk3RbujxZ0h1KnqP0uqQTlDxz6hVJk/O2WSNpQhrrE5IOTMtLJT2dntc0ffyspZykGyXNBkYDpwLj0nM6VNJFaXsskPSQpH3y4vmZpL+l8ZyVF8OotJ0WSLo5Ldvm+VoTkPWvbv3ya1d7AdV8fPeEaWnZxcD30uVWwHPAZ4EWwH5peXuSX8ML6Aq8lLfPMtJf1KfvbwOGpcsVwKi8dU8Ah6fLx5Hc5mXzGIcBt6XLk0nuZSaSxwr8H9Cb5MvmPKA0rRfAkHT52rztXwROSJevByamyzng53nHnAyclff+gLzlG4Bv5dV7ID1+D5LHrkDy7Ka/Afuk79s19Hz92vNfNTffM7OPrYvkztL5vgT0yfuWvz/JA/HeAG6UNIDktv+dgI47cMz7ofZu3/8f8EDeo2laNWD7hyMiJJUDb0dEebq/hSSJcX4a3/1p/d8Af5C0P9A2Iman5VNIEkmduOrRS9INQFugBHg0b90fI2IT8LKkmvb4IvCriPgIICL+9xOcr+1hnIzMGkYk3/wfrVOYDLUdCBwdEZXpHZf3LrB9FXWHxTevszb9txnJ82s2T4bbsiH9d1Pecs37+v7OG3LBeO1W1k0GTo+IBWk7lBWIBz5+1IEKHHNHz9f2ML5mZNYwjwL/kT4eAklHSGpD0kN6J01EJwKHpPU/BPbN234Z0ENSq7Q38oVCB4nk2UdLJf1behxJ6ttI59CMj+/+/HXgqYj4AFgt6XNp+VBgdqGN2fKc9gVWpG0ypAHH/wtwQd61pXZFPl/bjTgZmTXM3cDLwPOSXgJ+QdLj+C1wjKTnSD6QXwWIiPeAOZJekjQuIpYDvye5PvNbkrtX12cIMFzSAmAhjfdo+7VAT0nzSJ6Vc31afh7JxIQXgdK88s39Dhgp6QVJhwLfJ3mK7WOk5701ETGT5LEHzyl52ut301XFOl/bjXhqt1kT0RhT1s2KxT0jMzPLnHtGZmaWOfeMzMwsc05GZmaWOScjMzPLnJORmZllzsnIzMwy9/8AW64HTs7Li+UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gbm.plot_importance(clf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5e9424f510>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gbm.plot_importance(clf, dpi=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5e941c95d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2500x2500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gbm.plot_importance(clf, figsize=(10,10), dpi=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}