pima-classification-baseline-03.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/corazzon/boostcourse-ds-511/blob/master/pima-classification-baseline-03.ipynb)\n",
    "\n",
    "\n",
    "## 데이터셋 출처\n",
    "* [Pima Indians Diabetes Database | Kaggle](https://www.kaggle.com/uciml/pima-indians-diabetes-database)\n",
    "* https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_diabetes.html\n",
    "\n",
    "\n",
    "### 데이터 구성\n",
    "\n",
    "* Pregnancies : 임신 횟수\n",
    "* Glucose : 2시간 동안의 경구 포도당 내성 검사에서 혈장 포도당 농도 \n",
    "* BloodPressure : 이완기 혈압 (mm Hg)\n",
    "* SkinThickness : 삼두근 피부 주름 두께 (mm), 체지방을 추정하는데 사용되는 값\n",
    "* Insulin : 2시간 혈청 인슐린 (mu U / ml)\n",
    "* BMI : 체질량 지수 (체중kg / 키(m)^2)\n",
    "* DiabetesPedigreeFunction : 당뇨병 혈통 기능\n",
    "* Age : 나이\n",
    "* Outcome : 768개 중에 268개의 결과 클래스 변수(0 또는 1)는 1이고 나머지는 0입니다.\n",
    "\n",
    "\n",
    "## 필요한 라이브러리 로드"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 데이터 분석을 위한 pandas, 수치계산을 위한 numpy\n",
    "# 시각화를 위한 seaborn, matplotlib.pyplot 을 로드합니다. \n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 데이터셋 로드"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768, 16)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data/diabetes_feature.csv\")\n",
    "df.shape"
   ]
  },
  {
   "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",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "      <th>Pregnancies_high</th>\n",
       "      <th>Age_low</th>\n",
       "      <th>Age_middle</th>\n",
       "      <th>Age_high</th>\n",
       "      <th>Insulin_nan</th>\n",
       "      <th>Insulin_log</th>\n",
       "      <th>low_glu_insulin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>169.5</td>\n",
       "      <td>5.138735</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>102.5</td>\n",
       "      <td>4.639572</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>169.5</td>\n",
       "      <td>5.138735</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>94.0</td>\n",
       "      <td>4.553877</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>168.0</td>\n",
       "      <td>5.129899</td>\n",
       "      <td>False</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  Pregnancies_high  Age_low  \\\n",
       "0                     0.627   50        1             False    False   \n",
       "1                     0.351   31        0             False    False   \n",
       "2                     0.672   32        1              True    False   \n",
       "3                     0.167   21        0             False     True   \n",
       "4                     2.288   33        1             False    False   \n",
       "\n",
       "   Age_middle  Age_high  Insulin_nan  Insulin_log  low_glu_insulin  \n",
       "0        True     False        169.5     5.138735            False  \n",
       "1        True     False        102.5     4.639572             True  \n",
       "2        True     False        169.5     5.138735            False  \n",
       "3       False     False         94.0     4.553877             True  \n",
       "4        True     False        168.0     5.129899            False  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 데이터셋을 미리보기 합니다.\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 학습과 예측에 사용할 데이터셋 만들기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin',\n",
       "       'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome', 'Pregnancies_high',\n",
       "       'Age_low', 'Age_middle', 'Age_high', 'Insulin_nan', 'Insulin_log',\n",
       "       'low_glu_insulin'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768, 9)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df[['Glucose', 'BloodPressure', 'SkinThickness',\n",
    "       'BMI', 'DiabetesPedigreeFunction', 'Age', 'Pregnancies_high',\n",
    "       'Insulin_nan', 'low_glu_insulin']]\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768,)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = df['Outcome']\n",
    "y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 사이킷런에서 제공하는 model_selection 의 train_test_split 으로 만듭니다.\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((614, 9), (614,))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train 세트의 문제와 정답의 데이터 수를 확인해 주세요.\n",
    "\n",
    "X_train.shape, y_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((154, 9), (154,))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test 세트의 문제와 정답의 데이터 수를 확인해 주세요.\n",
    "\n",
    "X_test.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 머신러닝 알고리즘 사용하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
       "                       max_depth=11, max_features=None, max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
       "                       random_state=42, splitter='best')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# DecisionTree 를 불러옵니다.\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "model = DecisionTreeClassifier(max_depth=11, random_state=42)\n",
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 최적의 max_depth 값 찾기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 85.06493506493507\n",
      "4 87.66233766233766\n",
      "5 85.71428571428571\n",
      "6 81.81818181818183\n",
      "7 81.81818181818183\n",
      "8 81.81818181818183\n",
      "9 83.76623376623377\n",
      "10 79.22077922077922\n",
      "11 81.81818181818183\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "for max_depth in range(3, 12):\n",
    "    model = DecisionTreeClassifier(max_depth=max_depth, random_state=42)\n",
    "    y_predict = model.fit(X_train, y_train).predict(X_test)\n",
    "    score = accuracy_score(y_test, y_predict) * 100\n",
    "    print(max_depth, score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grid Search\n",
    "\n",
    "* https://scikit-learn.org/stable/modules/cross_validation.html\n",
    "* https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 45 candidates, totalling 225 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 4 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done  34 tasks      | elapsed:    3.5s\n",
      "[Parallel(n_jobs=-1)]: Done 225 out of 225 | elapsed:    4.0s finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score=nan,\n",
       "             estimator=DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None,\n",
       "                                              criterion='gini', max_depth=None,\n",
       "                                              max_features=None,\n",
       "                                              max_leaf_nodes=None,\n",
       "                                              min_impurity_decrease=0.0,\n",
       "                                              min_impurity_split=None,\n",
       "                                              min_samples_leaf=1,\n",
       "                                              min_samples_split=2,\n",
       "                                              min_weight_fraction_leaf=0.0,\n",
       "                                              presort='deprecated',\n",
       "                                              random_state=42,\n",
       "                                              splitter='best'),\n",
       "             iid='deprecated', n_jobs=-1,\n",
       "             param_grid={'max_depth': range(3, 12),\n",
       "                         'max_features': [0.3, 0.5, 0.7, 0.9, 1]},\n",
       "             pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n",
       "             scoring=None, verbose=2)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "\n",
    "model = DecisionTreeClassifier(random_state=42)\n",
    "param_grid = {\"max_depth\": range(3, 12), \n",
    "              \"max_features\": [0.3, 0.5, 0.7, 0.9, 1]}\n",
    "clf = GridSearchCV(model, param_grid=param_grid, n_jobs=-1, cv=5, verbose=2)\n",
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': 5, 'max_features': 0.7}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
       "                       max_depth=5, max_features=0.7, max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
       "                       random_state=42, splitter='best')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8664934026389444"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_max_depth</th>\n",
       "      <th>param_max_features</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>split4_test_score</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.006471</td>\n",
       "      <td>0.000485</td>\n",
       "      <td>0.002686</td>\n",
       "      <td>0.000658</td>\n",
       "      <td>5</td>\n",
       "      <td>0.7</td>\n",
       "      <td>{'max_depth': 5, 'max_features': 0.7}</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.910569</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.837398</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.866493</td>\n",
       "      <td>0.036082</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.006573</td>\n",
       "      <td>0.000491</td>\n",
       "      <td>0.002635</td>\n",
       "      <td>0.000312</td>\n",
       "      <td>4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>{'max_depth': 4, 'max_features': 0.7}</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.886179</td>\n",
       "      <td>0.829268</td>\n",
       "      <td>0.861789</td>\n",
       "      <td>0.918033</td>\n",
       "      <td>0.861655</td>\n",
       "      <td>0.037935</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.006613</td>\n",
       "      <td>0.000522</td>\n",
       "      <td>0.002681</td>\n",
       "      <td>0.000637</td>\n",
       "      <td>4</td>\n",
       "      <td>0.9</td>\n",
       "      <td>{'max_depth': 4, 'max_features': 0.9}</td>\n",
       "      <td>0.821138</td>\n",
       "      <td>0.886179</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.861615</td>\n",
       "      <td>0.026005</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.006644</td>\n",
       "      <td>0.000947</td>\n",
       "      <td>0.002781</td>\n",
       "      <td>0.000535</td>\n",
       "      <td>6</td>\n",
       "      <td>0.9</td>\n",
       "      <td>{'max_depth': 6, 'max_features': 0.9}</td>\n",
       "      <td>0.829268</td>\n",
       "      <td>0.894309</td>\n",
       "      <td>0.821138</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.877049</td>\n",
       "      <td>0.859963</td>\n",
       "      <td>0.029149</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.006094</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.002468</td>\n",
       "      <td>0.000401</td>\n",
       "      <td>8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>{'max_depth': 8, 'max_features': 0.7}</td>\n",
       "      <td>0.861789</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.837398</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.860656</td>\n",
       "      <td>0.858310</td>\n",
       "      <td>0.013162</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "12       0.006471      0.000485         0.002686        0.000658   \n",
       "7        0.006573      0.000491         0.002635        0.000312   \n",
       "8        0.006613      0.000522         0.002681        0.000637   \n",
       "18       0.006644      0.000947         0.002781        0.000535   \n",
       "27       0.006094      0.000273         0.002468        0.000401   \n",
       "\n",
       "   param_max_depth param_max_features                                 params  \\\n",
       "12               5                0.7  {'max_depth': 5, 'max_features': 0.7}   \n",
       "7                4                0.7  {'max_depth': 4, 'max_features': 0.7}   \n",
       "8                4                0.9  {'max_depth': 4, 'max_features': 0.9}   \n",
       "18               6                0.9  {'max_depth': 6, 'max_features': 0.9}   \n",
       "27               8                0.7  {'max_depth': 8, 'max_features': 0.7}   \n",
       "\n",
       "    split0_test_score  split1_test_score  split2_test_score  \\\n",
       "12           0.878049           0.910569           0.813008   \n",
       "7            0.813008           0.886179           0.829268   \n",
       "8            0.821138           0.886179           0.853659   \n",
       "18           0.829268           0.894309           0.821138   \n",
       "27           0.861789           0.878049           0.837398   \n",
       "\n",
       "    split3_test_score  split4_test_score  mean_test_score  std_test_score  \\\n",
       "12           0.837398           0.893443         0.866493        0.036082   \n",
       "7            0.861789           0.918033         0.861655        0.037935   \n",
       "8            0.853659           0.893443         0.861615        0.026005   \n",
       "18           0.878049           0.877049         0.859963        0.029149   \n",
       "27           0.853659           0.860656         0.858310        0.013162   \n",
       "\n",
       "    rank_test_score  \n",
       "12                1  \n",
       "7                 2  \n",
       "8                 3  \n",
       "18                4  \n",
       "27                5  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(clf.cv_results_).sort_values(by=\"rank_test_score\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1,\n",
       "       0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0,\n",
       "       0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1,\n",
       "       0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1,\n",
       "       0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1,\n",
       "       0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8701298701298701"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Search\n",
    "<img src=\"https://i.imgur.com/N17CPGj.png\">\n",
    "\n",
    "출처 : http://www.jmlr.org/papers/volume13/bergstra12a/bergstra12a.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
       "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
       "                       random_state=42, splitter='best')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3,  5,  8,  5,  5, 13,  5, 16, 18, 13])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_depth = np.random.randint(3, 20, 10)\n",
    "max_depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_features = np.random.uniform(0.7, 1.0, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': array([ 3,  5,  8,  5,  5, 13,  5, 16, 18, 13]),\n",
       " 'max_features': array([0.99106896, 0.81855538, 0.80462666, 0.98977458, 0.73282047,\n",
       "        0.82150853, 0.84194348, 0.88743413, 0.99886695, 0.87119353,\n",
       "        0.76534319, 0.80883467, 0.9150284 , 0.85429453, 0.77911168,\n",
       "        0.9210062 , 0.79638464, 0.99281375, 0.99780265, 0.84750491,\n",
       "        0.70992737, 0.9583918 , 0.75906882, 0.83963015, 0.75394577,\n",
       "        0.93916341, 0.86509081, 0.81393384, 0.91599864, 0.7415089 ,\n",
       "        0.85352664, 0.89897825, 0.83836258, 0.87044418, 0.72702334,\n",
       "        0.85906734, 0.8030263 , 0.81262126, 0.83317934, 0.84651679,\n",
       "        0.95067863, 0.77310569, 0.97842667, 0.78061133, 0.86059737,\n",
       "        0.83677233, 0.80382649, 0.8432214 , 0.9875819 , 0.82981433,\n",
       "        0.83095953, 0.87872657, 0.7961058 , 0.8113246 , 0.91099763,\n",
       "        0.79671905, 0.97237741, 0.90046943, 0.92105654, 0.82158186,\n",
       "        0.81755379, 0.8291375 , 0.85454379, 0.77120579, 0.7363162 ,\n",
       "        0.98492692, 0.75220163, 0.82488327, 0.87990592, 0.79613856,\n",
       "        0.94869687, 0.97880518, 0.81160924, 0.94770462, 0.71661541,\n",
       "        0.80342747, 0.89439379, 0.9379838 , 0.71543596, 0.87932605,\n",
       "        0.83239537, 0.97706006, 0.95202297, 0.75126108, 0.89816093,\n",
       "        0.93328139, 0.81298917, 0.89519292, 0.8643087 , 0.79294457,\n",
       "        0.91578112, 0.99709119, 0.78497154, 0.7200114 , 0.84726556,\n",
       "        0.80067696, 0.92617871, 0.82913264, 0.764748  , 0.75956455]),\n",
       " 'min_samples_split': [2, 3, 4, 5, 6]}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "param_distributions = {\"max_depth\" :max_depth, \n",
    "                       \"max_features\": max_features,\n",
    "                       \"min_samples_split\" : list(range(2, 7))\n",
    "                      }\n",
    "param_distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomizedSearchCV(cv=5, error_score=nan,\n",
       "                   estimator=DecisionTreeClassifier(ccp_alpha=0.0,\n",
       "                                                    class_weight=None,\n",
       "                                                    criterion='gini',\n",
       "                                                    max_depth=None,\n",
       "                                                    max_features=None,\n",
       "                                                    max_leaf_nodes=None,\n",
       "                                                    min_impurity_decrease=0.0,\n",
       "                                                    min_impurity_split=None,\n",
       "                                                    min_samples_leaf=1,\n",
       "                                                    min_samples_split=2,\n",
       "                                                    min_weight_fraction_leaf=0.0,\n",
       "                                                    presort='deprecated',\n",
       "                                                    random_state=42,\n",
       "                                                    splitter='best'),\n",
       "                   iid...\n",
       "       0.83239537, 0.97706006, 0.95202297, 0.75126108, 0.89816093,\n",
       "       0.93328139, 0.81298917, 0.89519292, 0.8643087 , 0.79294457,\n",
       "       0.91578112, 0.99709119, 0.78497154, 0.7200114 , 0.84726556,\n",
       "       0.80067696, 0.92617871, 0.82913264, 0.764748  , 0.75956455]),\n",
       "                                        'min_samples_split': [2, 3, 4, 5, 6]},\n",
       "                   pre_dispatch='2*n_jobs', random_state=42, refit=True,\n",
       "                   return_train_score=False, scoring='accuracy', verbose=0)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "\n",
    "clf = RandomizedSearchCV(model,\n",
    "                   param_distributions,\n",
    "                   n_iter=1000,\n",
    "                   scoring=\"accuracy\",\n",
    "                   n_jobs=-1,\n",
    "                   cv=5,\n",
    "                   random_state=42\n",
    "                  )\n",
    "\n",
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'min_samples_split': 4, 'max_features': 0.7415089045216909, 'max_depth': 5}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8697454351592697"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8701298701298701"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>param_min_samples_split</th>\n",
       "      <th>param_max_features</th>\n",
       "      <th>param_max_depth</th>\n",
       "      <th>params</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split3_test_score</th>\n",
       "      <th>split4_test_score</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>rank_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>772</th>\n",
       "      <td>0.006956</td>\n",
       "      <td>0.001394</td>\n",
       "      <td>0.002171</td>\n",
       "      <td>0.000143</td>\n",
       "      <td>4</td>\n",
       "      <td>0.752202</td>\n",
       "      <td>5</td>\n",
       "      <td>{'min_samples_split': 4, 'max_features': 0.752...</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.910569</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.869745</td>\n",
       "      <td>0.033985</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>731</th>\n",
       "      <td>0.022266</td>\n",
       "      <td>0.008578</td>\n",
       "      <td>0.005994</td>\n",
       "      <td>0.004555</td>\n",
       "      <td>4</td>\n",
       "      <td>0.709927</td>\n",
       "      <td>5</td>\n",
       "      <td>{'min_samples_split': 4, 'max_features': 0.709...</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.910569</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.869745</td>\n",
       "      <td>0.033985</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>0.024347</td>\n",
       "      <td>0.034837</td>\n",
       "      <td>0.008484</td>\n",
       "      <td>0.007401</td>\n",
       "      <td>4</td>\n",
       "      <td>0.73282</td>\n",
       "      <td>5</td>\n",
       "      <td>{'min_samples_split': 4, 'max_features': 0.732...</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.910569</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.869745</td>\n",
       "      <td>0.033985</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>687</th>\n",
       "      <td>0.005775</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>0.002380</td>\n",
       "      <td>0.000491</td>\n",
       "      <td>4</td>\n",
       "      <td>0.765343</td>\n",
       "      <td>5</td>\n",
       "      <td>{'min_samples_split': 4, 'max_features': 0.765...</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.910569</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.869745</td>\n",
       "      <td>0.033985</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>0.006005</td>\n",
       "      <td>0.001090</td>\n",
       "      <td>0.005060</td>\n",
       "      <td>0.005768</td>\n",
       "      <td>4</td>\n",
       "      <td>0.751261</td>\n",
       "      <td>5</td>\n",
       "      <td>{'min_samples_split': 4, 'max_features': 0.751...</td>\n",
       "      <td>0.878049</td>\n",
       "      <td>0.910569</td>\n",
       "      <td>0.813008</td>\n",
       "      <td>0.853659</td>\n",
       "      <td>0.893443</td>\n",
       "      <td>0.869745</td>\n",
       "      <td>0.033985</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     mean_fit_time  std_fit_time  mean_score_time  std_score_time  \\\n",
       "772       0.006956      0.001394         0.002171        0.000143   \n",
       "731       0.022266      0.008578         0.005994        0.004555   \n",
       "983       0.024347      0.034837         0.008484        0.007401   \n",
       "687       0.005775      0.000105         0.002380        0.000491   \n",
       "326       0.006005      0.001090         0.005060        0.005768   \n",
       "\n",
       "    param_min_samples_split param_max_features param_max_depth  \\\n",
       "772                       4           0.752202               5   \n",
       "731                       4           0.709927               5   \n",
       "983                       4            0.73282               5   \n",
       "687                       4           0.765343               5   \n",
       "326                       4           0.751261               5   \n",
       "\n",
       "                                                params  split0_test_score  \\\n",
       "772  {'min_samples_split': 4, 'max_features': 0.752...           0.878049   \n",
       "731  {'min_samples_split': 4, 'max_features': 0.709...           0.878049   \n",
       "983  {'min_samples_split': 4, 'max_features': 0.732...           0.878049   \n",
       "687  {'min_samples_split': 4, 'max_features': 0.765...           0.878049   \n",
       "326  {'min_samples_split': 4, 'max_features': 0.751...           0.878049   \n",
       "\n",
       "     split1_test_score  split2_test_score  split3_test_score  \\\n",
       "772           0.910569           0.813008           0.853659   \n",
       "731           0.910569           0.813008           0.853659   \n",
       "983           0.910569           0.813008           0.853659   \n",
       "687           0.910569           0.813008           0.853659   \n",
       "326           0.910569           0.813008           0.853659   \n",
       "\n",
       "     split4_test_score  mean_test_score  std_test_score  rank_test_score  \n",
       "772           0.893443         0.869745        0.033985                1  \n",
       "731           0.893443         0.869745        0.033985                1  \n",
       "983           0.893443         0.869745        0.033985                1  \n",
       "687           0.893443         0.869745        0.033985                1  \n",
       "326           0.893443         0.869745        0.033985                1  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(clf.cv_results_).sort_values(by=\"rank_test_score\").head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 학습과 예측하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
       "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
       "                       random_state=42, splitter='best')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 학습을 시킵니다.\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = X_train.columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import plot_tree\n",
    "\n",
    "plt.figure(figsize=(15, 15))\n",
    "tree = plot_tree(model, feature_names=feature_names, fontsize=10, filled=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0,\n",
       "       0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1,\n",
       "       0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0,\n",
       "       0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0,\n",
       "       0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0,\n",
       "       0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 예측을 하고 결과를 y_predict에 담습니다.\n",
    "y_predict = model.predict(X_test)\n",
    "y_predict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 정확도(Accuracy) 측정하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 다르게 예측한 갯수를 구해서 diff_count 에 할당해 줍니다.\n",
    "\n",
    "abs(y_predict - y_test).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "81.81818181818183"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# accuracy score를 구합니다.\n",
    "\n",
    "accuracy_score(y_test, y_predict) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.7.6"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}