03_SMOTE.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cca16ae9-e30b-437c-a935-c5cf0801d5b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "import seaborn as sns\n",
    "import sklearn.datasets as d\n",
    "import sklearn.model_selection as ms\n",
    "import sklearn.metrics as mt\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn import tree\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.tree import export_graphviz\n",
    "import pydot  #graphviz의 dot language 와의 인터페이스를 제공하는 패키지 임포트\n",
    "from IPython.display import Image #IPython의 display와 관련된 Pulbic API\n",
    "\n",
    "\n",
    "# 글씨체 보이기\n",
    "plt.rcParams['font.family'] = 'Malgun Gothic'\n",
    "matplotlib.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cda2ccc2",
   "metadata": {},
   "source": [
    "# 1. 데이터 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2299f810-0a9e-4300-a1d1-b0c35e469111",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 데이터 불러오기\n",
    "data = pd.read_csv(\"departure_data.csv\", encoding='euc-kr')\n",
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "90e45aea-e6da-418b-85d2-0aad177079aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 취소 데이터 확인하기\n",
    "df.loc[(df['현황'] == '취소') & (df['사유'] == '태풍'), '현황'] = '기상 취소'\n",
    "cancel_rows = df[df['현황'] == '취소']\n",
    "reason_counts = cancel_rows['사유'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "549d1c3c-3de8-439c-ad67-e4cd30066c09",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 지연 데이터 확인하기\n",
    "delay_rows = df[df['현황'] == '지연']\n",
    "reason_counts = cancel_rows['사유'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0435dfb2-6533-406b-8a43-d93ead3f6ddb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['최저운고'].fillna(0, inplace=True)\n",
    "df['강수량(mm)'].fillna(0, inplace=True)\n",
    "df['현황'].fillna('출발', inplace=True)\n",
    "\n",
    "# 기상 취소, 기상 지연의 이유가 아닌 행들을 삭제하는 코드\n",
    "# 취소에 사유가 없는 열 삭제\n",
    "df = df[(df['현황'] != '취소')]\n",
    "# 지연에 사유가 없는 열 삭제\n",
    "df = df[(df['현황'] != '지연') | (df['사유'].notna())]\n",
    "# 회항, 기상회항 삭제\n",
    "df = df[(df['현황'] != '회항')]\n",
    "df = df[(df['현황'] != '기상 회항')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "99aafa2c",
   "metadata": {
    "scrolled": false
   },
   "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>날짜</th>\n",
       "      <th>항공사</th>\n",
       "      <th>편명</th>\n",
       "      <th>출발공항코드</th>\n",
       "      <th>출발공항명</th>\n",
       "      <th>도착공항코드</th>\n",
       "      <th>도착공항명</th>\n",
       "      <th>계획시간</th>\n",
       "      <th>예상시간</th>\n",
       "      <th>출발시간</th>\n",
       "      <th>시간</th>\n",
       "      <th>온도</th>\n",
       "      <th>시정</th>\n",
       "      <th>전운량</th>\n",
       "      <th>최저운고</th>\n",
       "      <th>풍속</th>\n",
       "      <th>강수량(mm)</th>\n",
       "      <th>구분</th>\n",
       "      <th>현황</th>\n",
       "      <th>사유</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-01 00:00:00</td>\n",
       "      <td>아시아나항공</td>\n",
       "      <td>OZ286</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>SFO</td>\n",
       "      <td>샌프란시스코</td>\n",
       "      <td>00:05</td>\n",
       "      <td>23:40</td>\n",
       "      <td>00:07</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0.2</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>화물</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-01-01 00:00:00</td>\n",
       "      <td>에미레이트항공</td>\n",
       "      <td>EK323</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>DXB</td>\n",
       "      <td>두바이</td>\n",
       "      <td>00:10</td>\n",
       "      <td>23:50</td>\n",
       "      <td>00:40</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0.2</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-01 00:00:00</td>\n",
       "      <td>아시아나항공</td>\n",
       "      <td>OZ2041</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>LAX</td>\n",
       "      <td>로스앤젤레스</td>\n",
       "      <td>00:10</td>\n",
       "      <td>23:50</td>\n",
       "      <td>00:28</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0.2</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-01-01 00:00:00</td>\n",
       "      <td>싱가폴항공</td>\n",
       "      <td>SQ007</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>SIN</td>\n",
       "      <td>싱가포르</td>\n",
       "      <td>00:25</td>\n",
       "      <td>00:36</td>\n",
       "      <td>00:35</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0.2</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-01-01 00:00:00</td>\n",
       "      <td>터키항공</td>\n",
       "      <td>TK91</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>IST</td>\n",
       "      <td>아타튀르크</td>\n",
       "      <td>00:40</td>\n",
       "      <td>00:40</td>\n",
       "      <td>01:01</td>\n",
       "      <td>00:00</td>\n",
       "      <td>0.2</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585021</th>\n",
       "      <td>2019-12-31 00:00:00</td>\n",
       "      <td>아시아나항공</td>\n",
       "      <td>OZ286</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>SFO</td>\n",
       "      <td>샌프란시스코</td>\n",
       "      <td>23:30</td>\n",
       "      <td>23:30</td>\n",
       "      <td>23:42</td>\n",
       "      <td>23:00</td>\n",
       "      <td>-4.1</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>화물</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585022</th>\n",
       "      <td>2019-12-31 00:00:00</td>\n",
       "      <td>대한항공</td>\n",
       "      <td>KE319</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>CAN</td>\n",
       "      <td>광저우</td>\n",
       "      <td>23:35</td>\n",
       "      <td>23:35</td>\n",
       "      <td>23:33</td>\n",
       "      <td>23:00</td>\n",
       "      <td>-4.1</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>화물</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585023</th>\n",
       "      <td>2019-12-31 00:00:00</td>\n",
       "      <td>필리핀에어아시아</td>\n",
       "      <td>Z27047</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>CEB</td>\n",
       "      <td>세부</td>\n",
       "      <td>23:50</td>\n",
       "      <td>23:50</td>\n",
       "      <td>23:54</td>\n",
       "      <td>23:00</td>\n",
       "      <td>-4.1</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585024</th>\n",
       "      <td>2019-12-31 00:00:00</td>\n",
       "      <td>산동항공</td>\n",
       "      <td>SC4722</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>TAO</td>\n",
       "      <td>청도</td>\n",
       "      <td>23:50</td>\n",
       "      <td>23:50</td>\n",
       "      <td>23:56</td>\n",
       "      <td>23:00</td>\n",
       "      <td>-4.1</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585025</th>\n",
       "      <td>2019-12-31 00:00:00</td>\n",
       "      <td>에미레이트항공</td>\n",
       "      <td>EK323</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>DXB</td>\n",
       "      <td>두바이</td>\n",
       "      <td>23:50</td>\n",
       "      <td>23:50</td>\n",
       "      <td>23:51</td>\n",
       "      <td>23:00</td>\n",
       "      <td>-4.1</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>538124 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         날짜       항공사      편명 출발공항코드 출발공항명 도착공항코드   도착공항명  \\\n",
       "0       2017-01-01 00:00:00    아시아나항공   OZ286    ICN    인천    SFO  샌프란시스코   \n",
       "1       2017-01-01 00:00:00   에미레이트항공   EK323    ICN    인천    DXB     두바이   \n",
       "2       2017-01-01 00:00:00    아시아나항공  OZ2041    ICN    인천    LAX  로스앤젤레스   \n",
       "3       2017-01-01 00:00:00     싱가폴항공   SQ007    ICN    인천    SIN    싱가포르   \n",
       "4       2017-01-01 00:00:00      터키항공    TK91    ICN    인천    IST   아타튀르크   \n",
       "...                     ...       ...     ...    ...   ...    ...     ...   \n",
       "585021  2019-12-31 00:00:00    아시아나항공   OZ286    ICN    인천    SFO  샌프란시스코   \n",
       "585022  2019-12-31 00:00:00      대한항공   KE319    ICN    인천    CAN     광저우   \n",
       "585023  2019-12-31 00:00:00  필리핀에어아시아  Z27047    ICN    인천    CEB      세부   \n",
       "585024  2019-12-31 00:00:00      산동항공  SC4722    ICN    인천    TAO      청도   \n",
       "585025  2019-12-31 00:00:00   에미레이트항공   EK323    ICN    인천    DXB     두바이   \n",
       "\n",
       "         계획시간   예상시간   출발시간     시간   온도    시정  전운량  최저운고  풍속  강수량(mm)  구분  현황  \\\n",
       "0       00:05  23:40  00:07  00:00  0.2   450    2  30.0   2      0.0  화물  출발   \n",
       "1       00:10  23:50  00:40  00:00  0.2   450    2  30.0   2      0.0  여객  출발   \n",
       "2       00:10  23:50  00:28  00:00  0.2   450    2  30.0   2      0.0  여객  출발   \n",
       "3       00:25  00:36  00:35  00:00  0.2   450    2  30.0   2      0.0  여객  출발   \n",
       "4       00:40  00:40  01:01  00:00  0.2   450    2  30.0   2      0.0  여객  출발   \n",
       "...       ...    ...    ...    ...  ...   ...  ...   ...  ..      ...  ..  ..   \n",
       "585021  23:30  23:30  23:42  23:00 -4.1  1000    8  30.0   3      0.0  화물  출발   \n",
       "585022  23:35  23:35  23:33  23:00 -4.1  1000    8  30.0   3      0.0  화물  출발   \n",
       "585023  23:50  23:50  23:54  23:00 -4.1  1000    8  30.0   3      0.0  여객  출발   \n",
       "585024  23:50  23:50  23:56  23:00 -4.1  1000    8  30.0   3      0.0  여객  출발   \n",
       "585025  23:50  23:50  23:51  23:00 -4.1  1000    8  30.0   3      0.0  여객  출발   \n",
       "\n",
       "         사유  \n",
       "0       NaN  \n",
       "1       NaN  \n",
       "2       NaN  \n",
       "3       NaN  \n",
       "4       NaN  \n",
       "...     ...  \n",
       "585021  NaN  \n",
       "585022  NaN  \n",
       "585023  NaN  \n",
       "585024  NaN  \n",
       "585025  NaN  \n",
       "\n",
       "[538124 rows x 20 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a04b4c00",
   "metadata": {},
   "source": [
    "### 증폭 전 데이터 분포 시각화 하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "34db7506",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\AppData\\Local\\Temp\\ipykernel_5524\\3651330186.py:7: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
      "  plt.savefig('/Users/user/Documents/DataMining/termproject.png')\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:152: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 사용할 칼럼들을 추출 (기상 요건들과 운송 현황)\n",
    "selected = ['온도','시정', '전운량', '최저운고','풍속', '강수량(mm)', '현황']\n",
    "sdf = df[selected]\n",
    "\n",
    "sns.scatterplot(data=sdf, x=sdf.iloc[:, 0], y=sdf.iloc[:, 1], hue='현황')\n",
    "plt.title(\"증폭 전 데이터 분포\")\n",
    "plt.savefig('/Users/user/Documents/DataMining/termproject.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bfc73f0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counter({'출발': 532733, '기상 지연': 4918, '기상 취소': 473})\n"
     ]
    }
   ],
   "source": [
    "X = df[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "y = df['현황']\n",
    "from collections import Counter  \n",
    "counter = Counter(y)\n",
    "print(counter)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a5d76d4",
   "metadata": {},
   "source": [
    "# 2. SMOTE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b3b584ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "원본 데이터셋의 각 카테고리별 개수:\n",
      "출발       532733\n",
      "기상 지연      4918\n",
      "기상 취소       473\n",
      "Name: 현황, dtype: int64\n",
      "Counter({'출발': 532733, '기상 지연': 532733, '기상 취소': 532733})\n",
      "\n",
      "새로운 데이터셋의 각 카테고리별 개수:\n",
      "출발       532733\n",
      "기상 지연    532733\n",
      "기상 취소    532733\n",
      "Name: 현황, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 각 카테고리별 데이터 개수 출력\n",
    "print(\"원본 데이터셋의 각 카테고리별 개수:\")\n",
    "print(df['현황'].value_counts())\n",
    "\n",
    "# 출발 이외의 데이터를 추출\n",
    "non_departure_data = df[df['현황'] != '출발']\n",
    "\n",
    "# 출발 데이터만 따로 추출\n",
    "departure_data = df[df['현황'] == '출발']\n",
    "\n",
    "# 각 카테고리별 데이터 개수에 맞게 샘플링\n",
    "from imblearn.over_sampling import SMOTE\n",
    "smt = SMOTE(sampling_strategy='auto',random_state=42)\n",
    "\n",
    "# 데이터 증강\n",
    "X_sm, y_sm = smt.fit_resample(X,y)\n",
    "\n",
    "#클래스 수 파악 \n",
    "from collections import Counter  \n",
    "counter2 = Counter(y_sm)\n",
    "print(counter2)\n",
    "\n",
    "# # dataframe 연결\n",
    "X_sm = pd.DataFrame(X_sm)\n",
    "y_sm = pd.DataFrame(y_sm)\n",
    "smote_data = pd.concat([X_sm, y_sm], axis=1)\n",
    "\n",
    "# 새로운 데이터셋의 각 카테고리별 개수 출력\n",
    "print(\"\\n새로운 데이터셋의 각 카테고리별 개수:\")\n",
    "print(smote_data['현황'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "56a737a5",
   "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>온도</th>\n",
       "      <th>시정</th>\n",
       "      <th>전운량</th>\n",
       "      <th>최저운고</th>\n",
       "      <th>풍속</th>\n",
       "      <th>강수량(mm)</th>\n",
       "      <th>현황</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>450</td>\n",
       "      <td>2</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>출발</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1598194</th>\n",
       "      <td>26.900000</td>\n",
       "      <td>800</td>\n",
       "      <td>8</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>38</td>\n",
       "      <td>0.0</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1598195</th>\n",
       "      <td>26.310245</td>\n",
       "      <td>1000</td>\n",
       "      <td>7</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1598196</th>\n",
       "      <td>3.148633</td>\n",
       "      <td>1000</td>\n",
       "      <td>5</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1598197</th>\n",
       "      <td>22.010393</td>\n",
       "      <td>1000</td>\n",
       "      <td>7</td>\n",
       "      <td>9.740177</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1598198</th>\n",
       "      <td>21.900000</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1598199 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                온도    시정  전운량       최저운고  풍속  강수량(mm)     현황\n",
       "0         0.200000   450    2  30.000000   2      0.0     출발\n",
       "1         0.200000   450    2  30.000000   2      0.0     출발\n",
       "2         0.200000   450    2  30.000000   2      0.0     출발\n",
       "3         0.200000   450    2  30.000000   2      0.0     출발\n",
       "4         0.200000   450    2  30.000000   2      0.0     출발\n",
       "...            ...   ...  ...        ...  ..      ...    ...\n",
       "1598194  26.900000   800    8  30.000000  38      0.0  기상 취소\n",
       "1598195  26.310245  1000    7  40.000000   3      0.0  기상 취소\n",
       "1598196   3.148633  1000    5  30.000000  11      0.0  기상 취소\n",
       "1598197  22.010393  1000    7   9.740177   3      0.0  기상 취소\n",
       "1598198  21.900000  1000    8  30.000000  10      0.0  기상 취소\n",
       "\n",
       "[1598199 rows x 7 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smote_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f0c8487",
   "metadata": {},
   "source": [
    "### 증폭 후 데이터 분포 시각화 하기 (SMOTE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1f245151",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\AppData\\Local\\Temp\\ipykernel_5524\\2049536040.py:7: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
      "  plt.savefig('/Users/user/Documents/DataMining/termproject.png')\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\IPython\\core\\pylabtools.py:152: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 사용할 칼럼들을 추출 (기상 요건들과 운송 현황)\n",
    "selected = ['온도','시정', '전운량', '최저운고','풍속', '강수량(mm)', '현황']\n",
    "sdf2 = smote_data[selected]\n",
    "\n",
    "sns.scatterplot(data=sdf2, x=sdf2.iloc[:, 0], y=sdf2.iloc[:, 1], hue='현황')\n",
    "plt.title(\"SMOTE 증폭 이후 데이터 분포\")\n",
    "plt.savefig('/Users/user/Documents/DataMining/termproject.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bef5255a",
   "metadata": {},
   "source": [
    "# 3. train-test data set 설정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b3024319",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1118739, 6) (479460, 6) (1118739,) (479460,)\n"
     ]
    }
   ],
   "source": [
    "X = smote_data[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "y = smote_data['현황']\n",
    "#test, training (7:3 분할)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = 0.3, random_state = 100)\n",
    "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37920306",
   "metadata": {},
   "source": [
    "# 4. 모델링 - Decision Tree (원본 SMOTE Data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "743472e2",
   "metadata": {},
   "source": [
    "### Hyper Parameter Tuning - GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b93c37ab",
   "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>max_depth</th>\n",
       "      <th>min_samples_split</th>\n",
       "      <th>splitter</th>\n",
       "      <th>mean_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>30</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.944590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>25</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.940281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.928691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>30</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.928361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>25</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.925408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.919428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>25</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.915509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.909657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>30</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.908499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>25</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.906413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.903612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>25</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.897927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.895578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.884835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>30</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.879708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.877825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>25</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.875800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.855932</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    max_depth  min_samples_split splitter  mean_test_score\n",
       "12         30                 16     best         0.944590\n",
       "6          25                 16     best         0.940281\n",
       "14         30                 32     best         0.928691\n",
       "13         30                 16   random         0.928361\n",
       "8          25                 32     best         0.925408\n",
       "0          20                 16     best         0.919428\n",
       "7          25                 16   random         0.915509\n",
       "2          20                 32     best         0.909657\n",
       "16         30                 64     best         0.908499\n",
       "10         25                 64     best         0.906413\n",
       "15         30                 32   random         0.903612\n",
       "9          25                 32   random         0.897927\n",
       "4          20                 64     best         0.895578\n",
       "1          20                 16   random         0.884835\n",
       "17         30                 64   random         0.879708\n",
       "3          20                 32   random         0.877825\n",
       "11         25                 64   random         0.875800\n",
       "5          20                 64   random         0.855932"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "#테스트하고자 하는 파라미터 값들을 사전 타입으로 정의\n",
    "dt_clf = DecisionTreeClassifier(random_state = 33)\n",
    "parameters = {'max_depth': [20, 25, 30],\n",
    "              'min_samples_split': [16, 32, 64],\n",
    "              'splitter': ['best', 'random']}\n",
    "\n",
    "grid_dt = GridSearchCV(dt_clf, # estimator 객체,\n",
    "                      param_grid = parameters, cv = 5\n",
    "                      # n_jobs = -1: 모든 cpu를 사용)\n",
    "                      )\n",
    "\n",
    "grid_dt.fit(X_test, y_test)\n",
    "\n",
    "result = pd.DataFrame(grid_dt.cv_results_['params'])\n",
    "result['mean_test_score'] = grid_dt.cv_results_['mean_test_score']\n",
    "result.sort_values(by='mean_test_score', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f7114dc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=30, min_samples_split=16)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeClassifier</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeClassifier(max_depth=30, min_samples_split=16)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeClassifier(max_depth=30, min_samples_split=16)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_params = {'max_depth' : 30, 'min_samples_split': 16, 'splitter': 'best'}\n",
    "\n",
    "#최적 파라미터 조합으로 DecisionTreeClassifier 초기화\n",
    "best_dt = DecisionTreeClassifier(**best_params)\n",
    "\n",
    "#최적모델로 학습\n",
    "best_dt.fit(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2770fa69",
   "metadata": {},
   "source": [
    "### 교차검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f8b56819",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차검증 평균:  0.8466792911231178\n"
     ]
    }
   ],
   "source": [
    "#교차검증\n",
    "from sklearn.model_selection import cross_val_score, cross_validate\n",
    "\n",
    "#각 폴드의 스코어\n",
    "scores = cross_val_score(best_dt, X, y, cv = 5)\n",
    "scores\n",
    "\n",
    "pd.DataFrame(cross_validate(best_dt, X, y, cv = 5))\n",
    "print('교차검증 평균: ', scores.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f429636",
   "metadata": {},
   "source": [
    "### 학습결과평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2755c3cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "       기상 지연       0.96      0.96      0.96    159922\n",
      "       기상 취소       0.97      0.98      0.97    159874\n",
      "          출발       0.97      0.96      0.97    159664\n",
      "\n",
      "    accuracy                           0.97    479460\n",
      "   macro avg       0.97      0.97      0.97    479460\n",
      "weighted avg       0.97      0.97      0.97    479460\n",
      "\n",
      "Accuracy of Decision Tree:  0.9663079297543069\n"
     ]
    }
   ],
   "source": [
    "#학습결과평가\n",
    "from sklearn.metrics import classification_report\n",
    "best_dt.fit(X_test, y_test)\n",
    "predict_dt = best_dt.predict(X_test)\n",
    "print(classification_report(y_test, predict_dt, zero_division=0))\n",
    "accuracy = accuracy_score(y_test, predict_dt)\n",
    "print(\"Accuracy of Decision Tree: \", accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a92d3a2",
   "metadata": {},
   "source": [
    "# 4. 모델링 - Multinomial Logistic Regression (원본 SMOTE Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3b787f46",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score, roc_auc_score, roc_curve\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import statsmodels.api as sm\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5e18078f",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = smote_data[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "y = smote_data['현황']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "110cb7cc",
   "metadata": {},
   "source": [
    "### Hyper Parameter Tuning - GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1642f4a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Hyperparameters: {'C': 0.001, 'penalty': 'l2'}\n",
      "GridSearchCV Results:\n",
      "         C penalty  mean_test_score\n",
      "0   0.001      l2         0.598913\n",
      "3   1.000      l2         0.598816\n",
      "4  10.000      l2         0.598816\n",
      "2   0.100      l2         0.598813\n",
      "1   0.010      l2         0.598810\n"
     ]
    }
   ],
   "source": [
    "# 테스트하고자 하는 파라미터 값들을 사전 타입으로 정의\n",
    "mlr = LogisticRegression(random_state=42, multi_class='multinomial', solver='saga')\n",
    "parameters = {'C': [0.001, 0.01, 0.1, 1, 10], 'penalty': ['l2']}\n",
    "\n",
    "# 테스트와 훈련 데이터 분할\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=100)\n",
    "\n",
    "# 데이터 스케일 조정\n",
    "scaler = StandardScaler()\n",
    "X_train_scaled = scaler.fit_transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)\n",
    "\n",
    "# GridSearchCV를 사용하여 최적의 하이퍼파라미터 찾기\n",
    "grid_mlr = GridSearchCV(mlr, param_grid=parameters, cv=5)\n",
    "grid_mlr.fit(X_train_scaled, y_train)\n",
    "\n",
    "# 결과를 DataFrame으로 표시\n",
    "result = pd.DataFrame(grid_mlr.cv_results_['params'])\n",
    "result['mean_test_score'] = grid_mlr.cv_results_['mean_test_score']\n",
    "result.sort_values(by='mean_test_score', ascending=False, inplace=True)\n",
    "\n",
    "# 결과 출력\n",
    "print(\"Best Hyperparameters:\", grid_mlr.best_params_)\n",
    "print(\"GridSearchCV Results:\\n\", result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "509cc886",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(C=0.001, max_iter=1000, multi_class=&#x27;multinomial&#x27;,\n",
       "                   random_state=42, solver=&#x27;saga&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(C=0.001, max_iter=1000, multi_class=&#x27;multinomial&#x27;,\n",
       "                   random_state=42, solver=&#x27;saga&#x27;)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(C=0.001, max_iter=1000, multi_class='multinomial',\n",
       "                   random_state=42, solver='saga')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 최적의 하이퍼파라미터로 모델 생성\n",
    "best_mlr = LogisticRegression(random_state=42, multi_class='multinomial', solver='saga', max_iter = 1000, C=0.001, penalty='l2')\n",
    "best_mlr.fit(X_train_scaled, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82475afe",
   "metadata": {},
   "source": [
    "### 교차검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "248419e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차검증 평균:  0.5840217528706573\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>fit_time</th>\n",
       "      <th>score_time</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>76.712315</td>\n",
       "      <td>0.282501</td>\n",
       "      <td>0.587289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>77.317707</td>\n",
       "      <td>0.279248</td>\n",
       "      <td>0.594372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>76.186383</td>\n",
       "      <td>0.281950</td>\n",
       "      <td>0.557865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>78.311591</td>\n",
       "      <td>0.281195</td>\n",
       "      <td>0.615145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>76.307780</td>\n",
       "      <td>0.279845</td>\n",
       "      <td>0.565438</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    fit_time  score_time  test_score\n",
       "0  76.712315    0.282501    0.587289\n",
       "1  77.317707    0.279248    0.594372\n",
       "2  76.186383    0.281950    0.557865\n",
       "3  78.311591    0.281195    0.615145\n",
       "4  76.307780    0.279845    0.565438"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 교차검증\n",
    "from sklearn.model_selection import cross_val_score, cross_validate\n",
    "\n",
    "# 교차 검증 수행\n",
    "scores = cross_val_score(best_mlr, X, y, cv=5)\n",
    "cv_results = cross_validate(best_mlr, X, y, cv=5)\n",
    "\n",
    "print('교차검증 평균: ', scores.mean())\n",
    "pd.DataFrame(cv_results)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3464ed15",
   "metadata": {},
   "source": [
    "### 학습결과평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3ac13e60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "       기상 지연       0.65      0.64      0.65    159922\n",
      "       기상 취소       0.57      0.62      0.60    159874\n",
      "          출발       0.58      0.53      0.55    159664\n",
      "\n",
      "    accuracy                           0.60    479460\n",
      "   macro avg       0.60      0.60      0.60    479460\n",
      "weighted avg       0.60      0.60      0.60    479460\n",
      "\n",
      "Accuracy of Multinomial Logistic Regression:  0.5992658407374963\n"
     ]
    }
   ],
   "source": [
    "# 학습 결과 평가\n",
    "from sklearn.metrics import classification_report, accuracy_score\n",
    "predict_mlr = best_mlr.predict(X_test_scaled)\n",
    "print(classification_report(y_test, predict_mlr, zero_division=0))\n",
    "accuracy = accuracy_score(y_test, predict_mlr)\n",
    "print(\"Accuracy of Multinomial Logistic Regression: \", accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a10280a0",
   "metadata": {},
   "source": [
    "# 4. 모델링 - Random Forest (원본 SMOTE Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a8550856",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import sklearn.metrics as mt\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2059e8ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1118739, 6) (479460, 6) (1118739,) (479460,)\n"
     ]
    }
   ],
   "source": [
    "X = smote_data[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "y = smote_data['현황']\n",
    "#test, training (7:3 분할)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = 0.3, random_state = 100)\n",
    "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61d07055",
   "metadata": {},
   "source": [
    "### Hyper Parameter Tuning - GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "940d2f1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>max_depth</th>\n",
       "      <th>min_samples_split</th>\n",
       "      <th>n_estimators</th>\n",
       "      <th>mean_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.970007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.969995</td>\n",
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       "      <th>6</th>\n",
       "      <td>30</td>\n",
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       "      <td>0.969969</td>\n",
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       "      <td>130</td>\n",
       "      <td>0.969968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.969957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.969955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.969680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.969669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.969668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>130</td>\n",
       "      <td>0.969298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>0.969286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.969272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>0.956624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.956579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>130</td>\n",
       "      <td>0.956515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.956294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.956231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.956190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    max_depth  min_samples_split  n_estimators  mean_test_score\n",
       "10         30                  8           130         0.970007\n",
       "11         30                  8           140         0.969995\n",
       "6          30                  4           120         0.969969\n",
       "7          30                  4           130         0.969968\n",
       "9          30                  8           120         0.969957\n",
       "8          30                  4           140         0.969955\n",
       "17         40                  8           140         0.969680\n",
       "16         40                  8           130         0.969669\n",
       "15         40                  8           120         0.969668\n",
       "13         40                  4           130         0.969298\n",
       "12         40                  4           120         0.969286\n",
       "14         40                  4           140         0.969272\n",
       "0          20                  4           120         0.956624\n",
       "2          20                  4           140         0.956579\n",
       "1          20                  4           130         0.956515\n",
       "5          20                  8           140         0.956294\n",
       "3          20                  8           120         0.956231\n",
       "4          20                  8           130         0.956190"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#하이퍼 파라미터 튜닝(그리드 서치)4\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "#테스트하고자 하는 파라미터 값들을 사전 타입으로 정의\n",
    "rf6 = RandomForestClassifier(random_state=0)\n",
    "\n",
    "parameters = {'n_estimators': [120, 130, 140],\n",
    "              'max_depth': [20, 30, 40],\n",
    "              'min_samples_split': [4, 8]}\n",
    "\n",
    "grid_rf4 = GridSearchCV(rf6, # estimator 객체,\n",
    "                      param_grid = parameters, cv = 5\n",
    "                      # n_jobs = -1: 모든 cpu를 사용)\n",
    "                      )\n",
    "grid_rf4.fit(X_train, y_train)\n",
    "\n",
    "result = pd.DataFrame(grid_rf4.cv_results_['params'])\n",
    "result['mean_test_score'] = grid_rf4.cv_results_['mean_test_score']\n",
    "result.sort_values(by='mean_test_score', ascending=False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b3ff909b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Parameters for Random Forest: {'max_depth': 30, 'min_samples_split': 8, 'n_estimators': 130}\n",
      "Accuracy of the Best Random Forest model: 0.9714533016310015\n"
     ]
    }
   ],
   "source": [
    "best_params_rf = grid_rf4.best_params_  \n",
    "print(\"Best Parameters for Random Forest:\", best_params_rf)\n",
    "\n",
    "#최적 파라미터 조합으로 RandomForestClassifier 초기화\n",
    "best_rf = RandomForestClassifier(**best_params_rf)\n",
    "\n",
    "#최적모델로 학습\n",
    "best_rf.fit(X_train, y_train)\n",
    "\n",
    "# 최적 모델 평가\n",
    "predict3 = best_rf.predict(X_test)\n",
    "print(\"Accuracy of the Best Random Forest model:\", accuracy_score(y_test,predict3)) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "479ee734",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "### 교차검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ade80328",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차검증 평균:  0.8695863305247965\n"
     ]
    }
   ],
   "source": [
    "#교차검증: 검증데이터셋 나눠서 평가하기 (데이터셋: training, test, validation 으로 나눔)\n",
    "\n",
    "from sklearn.model_selection import cross_val_score, cross_validate\n",
    "\n",
    "#각 폴드의 스코어\n",
    "scores = cross_val_score(best_rf, X, y, cv = 5)\n",
    "scores\n",
    "\n",
    "pd.DataFrame(cross_validate(best_rf, X, y, cv = 5))\n",
    "print('교차검증 평균: ', scores.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6eb79380",
   "metadata": {},
   "source": [
    "### 학습 결과 평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0d8ac6ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Data:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "       기상 지연       0.96      0.96      0.96    159922\n",
      "       기상 취소       0.97      0.98      0.98    159874\n",
      "          출발       0.98      0.97      0.98    159664\n",
      "\n",
      "    accuracy                           0.97    479460\n",
      "   macro avg       0.97      0.97      0.97    479460\n",
      "weighted avg       0.97      0.97      0.97    479460\n",
      "\n"
     ]
    }
   ],
   "source": [
    "predict_test = best_rf.predict(X_test)\n",
    "\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "print('Test Data:\\n', classification_report(y_test, predict_test, zero_division=0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f70a5f10",
   "metadata": {},
   "source": [
    "### confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3e661001",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
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      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
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      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
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      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
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      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n",
      "findfont: Font family 'Malgun Gothic' not found.\n"
     ]
    },
    {
     "data": {
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ty6alucUPVrVqVvD390Hv3sNeSaTf5MmTp7Bv2wOVKhmic+d28F00Bzdu3MHRoyfRqHE96Ojo4OzZQ0rn6Onp4tE/iWT16jLExIYJdTo6OqhQQQdJyQlCmb//KizxX43S+G37XzgYfgxSqQUmeY7Bz7+sQtdP+5fq3qh0vvs+AJaWVXHs6G5IJBIkJaXgl19+x9SpE1FYWIiKFQ1Q++Na+PHHJVizxk84T0dHG+npT4TXcWfCUaPG82m0ovfi1EeJQv2x49Ho02dYqfqWePkaWrdxhJFRZfT7sid+Wr8MDg79P+xkhNSiVInI2bNnsWnTpleSEOD5/wyTJ09GixYt3trOzJkz4eXlpXz+w/f3l71J/dqIPX8JAPAsKwsAsOr7mbA0N1OK061QQfj372tffBI+d/EKlq37BRt/eJG8GVasKPzb3MwEjx6nKbX16HE6zM1MXtsna5klTI2NcPuenIlICbVo2QQWllVx/ESIUKajo4MOHdpg3PjhMDWpi8JiPkUpFApcv34LAHDu3AXUq18bU6dOxNGjJ1HJ0BD5+fno0L43CgoKlM7LzHwGAHjwIAn2bXsI5X37dkdfp88xauQkoezxP//9H6U8Rn5+PiwszZXasrCoiiTRp+KMjCfIyHiCa9duIjr6DO7dP4s+fRyxc+fuMvx0qCSys7MxdtxUTHSbAUvLqnjwIAmjRzsjI+MJHj58JCwonjBhOqJPnVE69+Xfjz59h6PCP+8XMpkU4f/7Ha3bvNixk5X1YvpHLk+GhaXylLmFhTnS0zOE0RAAyMvLE6YCz5w5D9tWzeDu4Qo3txmqufn/Go6IqE2pEhGpVIro6GjUr1+/2Pro6GhYWlq+tR09PT3o6ekpleVm/PenZV7n0tWbqFrFBADwcU1r6FaoAHlyyhunYWpUsxL+nfTwEXS0tZXKXtasYV1ExZ7HsH4v1olExpxFs4avX/Euf/gIaRlPULWKaSnv5sN1+NBxtG7VTaks6Ed/XE68hh9+CCo2CSmOlpYWdP+Zhjx7NgE6OjqoWrUKTpw4VWx8QUGBkMgAwMOHj5CVla1UViQvLw9nzsSjc+d2CNlzAMDzDwmdu7TDj0FbXtsniUQCiUTyXkyP/hfk5+fj3r3n63EGDuiLffvCoVAokJycgnv35LCxqYFft+967fm3b99TagvAa9cTRUXFonv3T5XKHLp2wknRFn8xLYkW9HQ/4N8HhULTPfhglCoRmTp1KsaOHYuYmBh07dpVSDqSkpIQHh6OdevWYcmSJe+ko5ryLCsLt+/Jhdf35Em4dPUGjCtXgpVlVSxfvxXJKY/w/YyvAQA//xGCalIL1K5ljZzcPPy5LxzRcfH4cfHz7X2GFQ3gMrAP/FZvQmGhAi2b1MeTp89wJuESKlWsiL6OnUvdx6Ff9sDIyXOxecdudGxri9BDx5Bw+Trmeo0X7mHNlp1w6NgW5mYmuHNfjh/W/oIaMinat2r+r39GH4qnTzNx4cJlpbLMzCykpqYJ5evWLcX9+0mYO/f5sPrUqRMRG3sO16/fgp6eLhwdu2DIkC+E7Z5Xr97A9l93Yd36HzBz5kKcjUuAedUq6NK5Pc7HX8T+UOUpm5JYEbgea9ctxZnY8zh9Og5u7q6oWLEifv55J4Dn2zn79++N/4VHIOVhKqpVk2LK1AnIysrG/v2lv96HzNCwImp/XEt4XauWNZo1bYjUx2m4c+c+Fn47AzKZFKNcPQEAderYoHWrFog+dQYmJsbwnDQGjRrVg+toT6GNBd8uxbIfFiA94wkOHDgEPV09tLRtClNTYwQErCt1H9eu+xkTJoyA7/ezsGnzdnTu3B79+/dCXycXIWbhtzMQuv8Q7ty5h8qVKmHwYCd88ok9evZyLuuPhqjESpWIuLm5wdzcHMuWLcPq1auFoUJtbW3Y2tpi06ZNGDhw4Fta+W9JSLyGUVPmCa/912wGAPTp1hnfebvj4aPHeJD8YmFgXl4+lgRtQXJKKvT1dFH3o5pY5+eDNi0aCzEeIwfDzNgI63/9E3d/SIZRpYpoUOcjjP7qyzL1sXmj+lg0axJWbtiOgA3bULOaFQIWTEcdmxoAnn8Cv3z9FnYfOIyMp89gUcUU9q2awX3EYOjqVnhL61Qa1a2robDwxSepioYGWLb8W1SrZoWsrGxcvnwNrqMm448/XkzvjBs3Dd4zPODrOxsymSUePXqM6Ogz+Pvv8DL14Y8/QmBe1Qyz50yGpWVVnDt3EU5OLkj+5/c0OycH7dq3hpvbSJiYGiM5OQXHj0Wj66f98PDho3/3A/jA2No2w//Cdgqvl/jPAwBs2bIDo8d4QSq1gPVLa8a0tbXh6TkWdes+X8x+5MgJfNK5L27devEckI0bf0XWsyx4eY3HIt9ZyMzMQnz8JaxYsb5Mfbx58w76Orlgif9cuLuPwt17DzBu/DSEhR0RYqpWNceGn5bDysoC6elPcD7+Inr2ckZ4+NEyXfO9wKkZtZEoFGUbf8rLy0NKyvM3NnNzc2G+sqxy757/V+fT+8W0bm9Nd4HKkbyCfE13gcqZNz3ETRWyts5RWVsGzt++PegDVubvmqlQoQKsrIpfs0BERERUEvzSOyIiIjE+0ExtmIgQERGJcY2I2jARISIiEuP2XbXhl94RERGRxnBEhIiISIxTM2rDRISIiEiMiYjacGqGiIiINIYjIkRERGLcvqs2TESIiIhEFIXcNaMunJohIiIijeGICBERkRgXq6oNExEiIiIxrhFRG07NEBERkcZwRISIiEiMi1XVhokIERGRGNeIqA2nZoiIiMQKC1V3lEJERAR69+4NmUwGiUSC4OBgoS4vLw/e3t5o0qQJDA0NIZPJMHz4cNy/f1+pjdTUVDg7O8PIyAgmJiZwdXXF06dPlWLOnTuHjh07Ql9fH9bW1vDz83ulLzt37kT9+vWhr6+PJk2aYN++fUr1CoUCPj4+sLKygoGBARwcHHDlypVS3S/ARISIiKjcyMzMRLNmzbBq1apX6p49e4bY2FjMmTMHsbGx+PPPP5GYmIg+ffooxTk7OyMhIQFhYWEICQlBREQExo4dK9RnZGSgW7duqFmzJmJiYuDv74958+Zh7dq1QsyJEycwZMgQuLq64syZM3BycoKTkxPi4+OFGD8/PwQGBiIoKAhRUVEwNDSEo6MjsrOzS3XPEoWifHzXce7d85ruApUjpnV7a7oLVI7kFeRrugtUzuTm3H2n7T9bPk5lbVX0/LFM50kkEuzatQtOTk6vjTl16hTatGmDW7duoUaNGrh48SIaNmyIU6dOoVWrVgCA0NBQ9OjRA3fv3oVMJsOaNWswa9YsyOVy6OrqAgBmzJiB4OBgXLp0CQAwaNAgZGZmIiQkRLhW27Zt0bx5cwQFBUGhUEAmk2HKlCmYOnUqACA9PR2WlpbYtGkTBg8eXOL75IgIERGRmAqnZnJycpCRkaF05OTkqKSb6enpkEgkMDExAQBERkbCxMRESEIAwMHBAVpaWoiKihJiOnXqJCQhAODo6IjExEQ8fvxYiHFwcFC6lqOjIyIjIwEAN27cgFwuV4oxNjaGnZ2dEFNSTESIiIjeIV9fXxgbGysdvr6+/7rd7OxseHt7Y8iQITAyMgIAyOVyWFhYKMXp6OjAzMwMcrlciLG0tFSKKXr9tpiX618+r7iYkuKuGSIiIjEVbt+dOXMmvLy8lMr09PT+VZt5eXkYOHAgFAoF1qxZ86/a0jQmIkRERGIqfLKqnp7ev048XlaUhNy6dQsHDx4URkMAQCqVIjk5WSk+Pz8fqampkEqlQkxSUpJSTNHrt8W8XF9UZmVlpRTTvHnzUt0Pp2aIiIj+I4qSkCtXruB///sfqlSpolRvb2+PtLQ0xMTECGUHDx5EYWEh7OzshJiIiAjk5eUJMWFhYahXrx5MTU2FmPDwcKW2w8LCYG9vDwCwsbGBVCpVisnIyEBUVJQQU1JMRIiIiMQKFao7SuHp06eIi4tDXFwcgOeLQuPi4nD79m3k5eWhf//+OH36NLZu3YqCggLI5XLI5XLk5uYCABo0aIDu3btjzJgxiI6OxvHjx+Hu7o7BgwdDJpMBAL766ivo6urC1dUVCQkJ+O233xAQEKA0fTRp0iSEhoZi6dKluHTpEubNm4fTp0/D3d0dwPMdPZ6enli4cCF2796N8+fPY/jw4ZDJZG/c5VMcbt+lconbd+ll3L5LYu96+26mr4vK2jKcubnEsYcPH0aXLl1eKXdxccG8efNgY2NT7HmHDh1C586dATx/oJm7uzv27NkDLS0t9OvXD4GBgahUqZIQf+7cObi5ueHUqVMwNzeHh4cHvL29ldrcuXMnZs+ejZs3b6JOnTrw8/NDjx49hHqFQoG5c+di7dq1SEtLQ4cOHbB69WrUrVu3xPcLMBGhcoqJCL2MiQiJva+JyIeIi1WJiIjE+KV3asNEhIiISEyFu2bozZiIEBERiXFERG24a4aIiIg0hiMiREREYoWcmlEXJiJERERinJpRG07NEBERkcZwRISIiEiMu2bUhokIERGRGKdm1IZTM0RERKQxHBEhIiISUXDXjNowESEiIhLj1IzacGqGiIiINIYjIkRERGIcEVEbJiJERERi3L6rNkxEiIiIxDgiojZcI0JEREQawxERIiIiEQVHRNSGiQgREZEYExG14dQMERERaQxHRIiIiMT4ZFW1YSJCREQkxqkZteHUDBEREWkMR0SIiIjEOCKiNkxEiIiIRBQKJiLqwqkZIiIi0hiOiBAREYlxakZtmIgQERGJMRFRGyYiREREInzEu/qUm0Sk0sefa7oLVI5k3ovQdBeoHDGQddR0F4joHSk3iQgREVG5wRERtWEiQkREJMYnvKsNt+8SERGRxnBEhIiISISLVdWHiQgREZEYExG14dQMERERaQwTESIiIrFCFR6lEBERgd69e0Mmk0EikSA4OFipXqFQwMfHB1ZWVjAwMICDgwOuXLmiFJOamgpnZ2cYGRnBxMQErq6uePr0qVLMuXPn0LFjR+jr68Pa2hp+fn6v9GXnzp2oX78+9PX10aRJE+zbt6/UfSkJJiJEREQiikKFyo7SyMzMRLNmzbBq1api6/38/BAYGIigoCBERUXB0NAQjo6OyM7OFmKcnZ2RkJCAsLAwhISEICIiAmPHjhXqMzIy0K1bN9SsWRMxMTHw9/fHvHnzsHbtWiHmxIkTGDJkCFxdXXHmzBk4OTnByckJ8fHxpepLSUgU5eQrBnX1qmu6C1SO8IFm9DI+0IzE8nPvvdP2Hw/orLK2THceLtN5EokEu3btgpOTE4DnIxAymQxTpkzB1KlTAQDp6emwtLTEpk2bMHjwYFy8eBENGzbEqVOn0KpVKwBAaGgoevTogbt370Imk2HNmjWYNWsW5HI5dHV1AQAzZsxAcHAwLl26BAAYNGgQMjMzERISIvSnbdu2aN68OYKCgkrUl5LiiAgREZGYCqdmcnJykJGRoXTk5OSUuks3btyAXC6Hg4ODUGZsbAw7OztERkYCACIjI2FiYiIkIQDg4OAALS0tREVFCTGdOnUSkhAAcHR0RGJiIh4/fizEvHydopii65SkLyXFRISIiEhElVMzvr6+MDY2Vjp8fX1L3Se5XA4AsLS0VCq3tLQU6uRyOSwsLJTqdXR0YGZmphRTXBsvX+N1MS/Xv60vJcXtu0RERGIqfLLqzJkz4eXlpVSmp6enugv8x3FEhIiI6B3S09ODkZGR0lGWREQqlQIAkpKSlMqTkpKEOqlUiuTkZKX6/Px8pKamKsUU18bL13hdzMv1b+tLSTERISIiElEUqu5QFRsbG0ilUoSHhwtlGRkZiIqKgr29PQDA3t4eaWlpiImJEWIOHjyIwsJC2NnZCTERERHIy8sTYsLCwlCvXj2YmpoKMS9fpyim6Dol6UtJMREhIiIS09BzRJ4+fYq4uDjExcUBeL4oNC4uDrdv34ZEIoGnpycWLlyI3bt34/z58xg+fDhkMpmws6ZBgwbo3r07xowZg+joaBw/fhzu7u4YPHgwZDIZAOCrr76Crq4uXF1dkZCQgN9++w0BAQFK00eTJk1CaGgoli5dikuXLmHevHk4ffo03N3dAaBEfSkprhEhIiIqJ06fPo0uXboIr4uSAxcXF2zatAnTp09HZmYmxo4di7S0NHTo0AGhoaHQ19cXztm6dSvc3d3RtWtXaGlpoV+/fggMDBTqjY2NceDAAbi5ucHW1hbm5ubw8fFRetZIu3btsG3bNsyePRvffPMN6tSpg+DgYDRu3FiIKUlfSoLPEaFyic8RoZfxOSIk9q6fI5Ly+Scqa8v87yMqa+t9xBERIiIiMRWu7aA34xoRIiIi0hiOiBAREYmocrcLvRkTESIiIhEmIurDRISIiEiEiYj6cI0IERERaQxHRIiIiMQUEk334IPBRISIiEiEUzPqw6kZIiIi0hiOiBAREYkoCjk1oy5MRIiIiEQ4NaM+nJohIiIijeGICBERkYiCu2bUhokIERGRCKdm1IdTM0RERKQxHBEhIiIS4a4Z9WEiQkREJKJQaLoHHw4mIkRERCIcEVEfrhEhIiIijeGICBERkQhHRNSHiQgREZEI14ioD6dmiIiISGM4IkJERCTCqRn1YSJCREQkwke8qw+nZoiIiEhjOCJCREQkwu+aUR8mIkRERCKFnJpRG07NEBERkcZwRISIiEiEi1XVh4kIERGRCLfvqg8TESIiIhE+WVV9uEaEiIiINIYjIkRERCKcmlEfJiJEREQi3L6rPpyaISIiIo3hiAgREZEIt++qD0dEiIiIRBQK1R2lUVBQgDlz5sDGxgYGBgb4+OOP8e2330LxUkMKhQI+Pj6wsrKCgYEBHBwccOXKFaV2UlNT4ezsDCMjI5iYmMDV1RVPnz5Vijl37hw6duwIfX19WFtbw8/P75X+7Ny5E/Xr14e+vj6aNGmCffv2le6GSoCJCBERUTmxePFirFmzBitXrsTFixexePFi+Pn5YcWKFUKMn58fAgMDERQUhKioKBgaGsLR0RHZ2dlCjLOzMxISEhAWFoaQkBBERERg7NixQn1GRga6deuGmjVrIiYmBv7+/pg3bx7Wrl0rxJw4cQJDhgyBq6srzpw5AycnJzg5OSE+Pl6l98xE5A2mT3PDieMheJRyCXfvxOH3netRt+5HbzzHqe/niDyxF8lJCXicehmnovfD+at+77yv48e74HJiJDLSr+LY0T1o1aq5Uv2qVYtw8eIxpKddxb27Z/HH7z+hXr2P33m/3jen487DbfpcdOnjjMbtP0d4xIm3npObm4uAHzfhsy9d0KJzb3Tr54I/Q/a/035Gx57DgJHuaNG5Nz4fOArBe8OU6lf99Asat/9c6eg9ZMw77dP7SiaTYvOmQCQ9iMeT9Ks4E/s/2LZs+sZzdHV18e0Cb1y7EoXMJ9dx9fJJjHAZ9E77+Ukne0RHhSLzyXVcunAMw4cNVKr3nu6OyBN78fhRIu7/8x5Rt+6H+x5RqJCo7CiNEydOoG/fvujZsydq1aqF/v37o1u3boiOjgbwfDRk+fLlmD17Nvr27YumTZtiy5YtuH//PoKDgwEAFy9eRGhoKNavXw87Ozt06NABK1aswPbt23H//n0AwNatW5Gbm4sNGzagUaNGGDx4ML7++mv88MMPQl8CAgLQvXt3TJs2DQ0aNMC3336Lli1bYuXKlar5If+DicgbdOxkjzVBm9GxYx/06DEEOhUqYG/INlSsaPDac1Ifp2HRohXo9Elf2Lb6DJu37MC6dUvx2WeflLkfw4YNQNiBna+tH9C/N/z9fLDwu2Wws/sc585fwN6QX1C1ahUhJjb2PMaMmYKmzTqjZy9nSCQS7A3ZBi0t/gqURlZWNurV/gizpkws8TlT5vgi6nQcFsz0RMiv6+E3fwZq1ahe5j7ce5CExu0/f2393ftyuE3zQZuWzfD7plUYNtAJcxcvx/GoGKW42jY1cXj3VuHYsmZJmfv0oTIxMUbE4WDk5eWjV++haNKsC6ZPX4DHaelvPG/7r0H4tEsHjB03FQ0bd8LQYW64fPlamftRs2Z15Ofee219rVrW2P3XFhw5fAK2rbshcMV6rP3RH91eel/q1LEt1qzZjPYde6N7jyGooFMBf+998/vd+0yhkKjsKI127dohPDwcly9fBgCcPXsWx44dw+efP/9//saNG5DL5XBwcBDOMTY2hp2dHSIjIwEAkZGRMDExQatWrYQYBwcHaGlpISoqSojp1KkTdHV1hRhHR0ckJibi8ePHQszL1ymKKbqOqnCx6hv07j1U6fXo0ZNx/945tGzZFMeORRV7TkSE8n+glSt/wrCh/dG+XWuEhR0B8PzT0IIF0zFooBNMTIyQkJCIb2Z9/8q5JTVp0lj8tOFXbNmyAwDg5jYDn3fvihEug+G/ZBUA4Keftgrxt27dxdy5/oiJCUOtWta4fv1Wma77Iepo3xod7VuXOP7YydM4HXceoTs3wtioMgCgmpXlK3G/7w7F5u1/4t4DOapJLeE8oC8Gf9mrTH3cEbwX1aykmObxfITj41o1EHsuAVt+24X2drZCnLa2NsyrmJXpGvTc9GkTcffufYwe4yWU3bx5543nOHbrjE4d26JOvXZ4/DgNwPP/J8VGjRyCyZPHwaaWNW7euouVKzcg6MfNZernuLHDcOPmbUzzXgAAuHTpKtq3b4NJX4/BgX/el3qK3u9GjfaE/P552LZsiqOveb+jksnJyUFOTo5SmZ6eHvT09F6JnTFjBjIyMlC/fn1oa2ujoKAA3333HZydnQEAcrkcAGBpqfw+YmlpKdTJ5XJYWFgo1evo6MDMzEwpxsbG5pU2iupMTU0hl8vfeB1V4cfhUjA2NgIAPE5NK/E5Xbq0R926Hyv9jxywfCHa2tli6LCJsG31Gf74MwQhe35G7do2b2ipeBUqVEDLlk1w8OBRoUyhUODgwaNo27ZlsedUrGiA4S4Dcf3GLdy5c7/U16SSO3TsJBrVr4MNW3fi075D0XPwaPivXIfsl96UQvYfxKr1P+PrsS7YvXUtvh43AivWbcFf+8Le0PLrnY2/hLaiqbn2drY4G39Rqez23Xvo0scZ3QeMhPe8xXggTy7T9T5kvXp1Q0zMOWz/9Ufcv3sWp6L3w3XUVyU6Z9rUCbh14zQuJByF36I50NfXF2KGDPkC8+ZOxRyfxWjctDNmz1mE+fOmYdiwAWXqZ1s7W4SHH1MqO3DgMNq2tX3NGS/e71L/SZY+NKpcrOrr6wtjY2Olw9fXt9jr7tixA1u3bsW2bdsQGxuLzZs3Y8mSJdi8uWxJ6H+BykdE7ty5g7lz52LDhg2vjSkuO1QoFJBIyu92KYlEgiVL5uH48WgkXEh8Y6yRUWXcvHEaenq6KCgogMfXsxAe/jxRsLaWwcVlID6ubYcHD5IAAMuW/Yhu3TrDZfhAzPFZXKp+mZubQUdHB0lJD5XKk5NTUK9ebaWyceOGw/f7WahUyRCJiVfRo8dXyMvLK9X1qHTu3pcj9lwCdHV1EeA7B4/T0rFw6Sqkpz/BwlnPP0Wv+ukXTPMYg886twcAVJdJcf3mbez462/07fFZqa+ZkvoYVcxMlcqqmJrgaeYzZOfkQF9PD00b1sPCWVNQq0Z1pDxKxeoNWzF84jQE/7wGhoYV//2NfyA+sqmBceOGYXnAOixaHIhWts2xfNkC5Obl4eefi59O/cimBtq3b43s7Bz0HzAa5uZmWBH4PcyqmAojK3PnTME07wUIDv4bwPNRloYN6mLs6KGvbfdNLKUWSE5+9T3C2NgI+vr6Soscgefvdz8smf/8/S7hze937ytVPtBs5syZ8PLyUiorbjQEAKZNm4YZM2Zg8ODBAIAmTZrg1q1b8PX1hYuLC6RSKQAgKSkJVlZWwnlJSUlo3rw5AEAqlSI5WfmDRX5+PlJTU4XzpVIpkpKSlGKKXr8tpqheVVSeiKSmpmLz5s1vTER8fX0xf/58pTItrcrQ1jFSdXdUJjDwOzRqWA9dPv3yrbFPnjxF6zaOqGRYEV0+7QB/Px/cuHEbERGRaNy4PnR0dJAQH6F0jp6eLlIfPZ+Xs7aW4WzcIaFOR0cbFSpUQOqjF28IixevwGK/0i0Y+vXXXQgPPwqp1AJek8dh29Y1+KTzF68khaQ6hYWFkECCxXOno3IlQwDAtNw8eM3+DrOnuqGwUIE79x7Ax3c55i4OEM4rKChAJUND4XVf53G4n/TPG8s/2/haO3wh1Ns2a4ygpd+WuF8vTy/Vq22DJg3roVs/F4QePIp+vR3LdK8fIi0tLcTEnMPsOYsAAHFxCWjUqB7GjRn22oRBS0sLCoUCw1zckZHxBAAwdfp87Ni+Fu4e30BLS4LatW2w7sel+HGNv3Cejo420tOfCK/Pxh1EzX/WGhV9iEtLvSzUHzsWhV59hpXpvlYEfo9Gjerhky5fvD34PaXK54i8bhqmOM+ePXtl7Z62tjYKCwsBADY2NpBKpQgPDxcSj4yMDERFRWHChAkAAHt7e6SlpSEmJga2ts9HvQ4ePIjCwkLY2dkJMbNmzUJeXh4qVKgAAAgLC0O9evVgamoqxISHh8PT01PoS1hYGOzt7cv2g3iNUiciu3fvfmP99evX39pGcdlhFfMGpe2K2ixfvhA9PndAV4d+uHfvwVvjFQoFrl27CQA4e+4C6terg+nT3RAREYlKhobIz89HW/vPUVBQqHTe06eZAID795PQus2LPwZOTp/jC6cecBnhIZSl/jM9lJKSivz8fFhaVlVqy8LCHElJyhlxRsYTZGQ8wdWrNxAVFYvkpAQ49e2O33b8VeKfBZVO1SpmsKhaRUhCAOCjWtZQKBRISk4RRh/meX+Npo3qK5378pvRmqULkJ9fAABIepiCke7e+GPTKqFeT+/FgjNzM1M8Sn2s1Najx2moZFgR+q95MzSqXAk1ravh9l1O1ZXGgwfJuHDxslLZpUtX8eUXPV5/jjwZ9+7JhSTk+TlXoKWlherVrYTycROmITr6jNK5BQUFwr979xkm/AGpJpPiYPgfsG3dTajPynoxypEkT4aFxavvEenpGa+MhgQsX4iePRzQpeuXJXq/I9Xq3bs3vvvuO9SoUQONGjXCmTNn8MMPP2DUqFEAniednp6eWLhwIerUqQMbGxvMmTMHMpkMTk5OAIAGDRqge/fuGDNmDIKCgpCXlwd3d3cMHjwYMpkMAPDVV19h/vz5cHV1hbe3N+Lj4xEQEIBly5YJfZk0aRI++eQTLF26FD179sT27dtx+vRppS2+qlDqRMTJyQkSiUTp4Spib5tiKS47LK/TMsuXL0TfPt3xWbcBb12E9jpaWhLo6T6/37iz8dDR0UHVquY4fjy62PiCggIhkQGeD6FmZWUrlRXJy8tDbOx5dOnSAbt3P98SKpFI0KVLB6xZs+m1fZJIJJBIJNB96Q8YqV6Lpg1x4NAxPHuWJew+uHXnHrS0tGBpYQ59PT1YmFfB3fty9HL89LXtyKQvFoxpa2sDAGpUlxUb26xxfRyNPK1UFnnqDJo1fn2y/+xZFu7ce4De3buW+N4IOBF5CvVEW1zr1vkIt2+/fgfLiROn0L9fLxgaVkRm5jMAQJ06H6GgoAB37z5AdnY27t17gI9sauLXX3e9tp2Xr5Gfnw8Axb5HAMDJqBh07678++Xg0AknTyrvpApYvhBOfbuj62dlf797X2jqu2ZWrFiBOXPmYOLEiUhOToZMJsO4cePg4+MjxEyfPh2ZmZkYO3Ys0tLS0KFDB4SGhiqtM9q6dSvc3d3RtWtXaGlpoV+/fggMDBTqjY2NceDAAbi5ucHW1hbm5ubw8fFRetZIu3btsG3bNsyePRvffPMN6tSpg+DgYDRu3Fil91zqRMTKygqrV69G3759i62Pi4sThoL+6wIDv8PgQU7o198VT548FUYd0tOfCJ8iNvy0HPfvy4Wh2enT3BATew7Xr9+Cnp4uunf/FM7O/eDu8Q0A4MqVG9i27U9s2LAc3tO/RdzZeJibV8GnXdrjfPxF/P33wVL3MyBgLX76aRliY87i1Ok4eHiMhqGhATZv+Q0AYGNTAwP690bY/yKQkvII1apZYfo0N2RlZSM0tPTX+5A9e5alNGpw734SLl2+BmOjyrCSWmDZmo1ITnkE3zlTAQA9P+uCoE2/Yvb3P8DNdSgep2dg6aqf8EXPbsLoxETXoVi0PAiVKhmig50tcvPykHDpCjKePIXL4LdPBYoNdOqJX//Y8/w6vbohOuYs9h+MwGr/BUKM/8p16NzeDjKpJZJTHmHV+l+gra2FHg5l32b+IQoIWIejEX9hhrcHdv6+B61bN8fo0c4YP3G6EPPdwhmQyawwctQkAMCv23dh1jee+Gn9MsxfsATmVcyweNEcbNy0XXhfmb9gKZYv+xbp6RnYf+Aw9PR0YduyKUxNTbA8oPSfRn9c+zMmThiJRb6zsHHTdnTp3AED+vdGn77DhZgVgd9jyGAnfNlv1Gvf7z4kpXwgqspUrlwZy5cvx/Lly18bI5FIsGDBAixYsOC1MWZmZti2bdsbr9W0aVMcPXr0jTEDBgzAgAFlWyRdUqVORGxtbRETE/PaRORtoyX/JePHuQAAwv/3u1K56+jJwvyvtXU1Ye4OAAwNKyIw8HtUr2aFrKxsJCZexYgRX2Pn73uEmNFjvPDNzElY7DcH1WRSpKSkIjr6DPbtCy9TP3f+vgfmVavAx2cqpNKqOHv2Anr1Hobk5BQAQHZ2Dtp3sIOHx2iYmhojKSkFx45F4ZPOffHw4aMyXfNDFX/pCkZ5eAuv/VY8/6PQ93MHfDd7ClIepeLBS1NiFSsaYN3y7/H9D2swyHUSjI0ro/unneAx9sUfgP59usNAXw8bt/2OpavWw0BfH3U/roWhA53K1MfqMilW+S+AX+CP+GVnMCyrmmO+t6fS1t2k5BRMn7sYaRkZMDMxRoumjbD1x2UwMzUp0zU/VKdjzqL/gNFYuHAGZs/yxI2bd+A1Za7SSIZUaoka1i9GrzIzn6F7j8EIWLYQUZF/49Gjx/j99z2YM/fF47U3bPwVz7KyMMVrAhYvmo3MzGeIj7+EgBXry9TPmzfvoE/f4ViyZB483F1x9+4DjB03Tdi6CwATxj9/vzsY/ofSuaNcJ2PLzzvKdF2ikpAoSpk1HD16FJmZmejevXux9ZmZmTh9+jQ++aR0n6x09cr+gCd6/2Tei3h7EH0wDGQdNd0FKmfe9AA3VThhpbonYrd78Mfbgz5gpR4R6djxzW8IhoaGpU5CiIiIyhN++6768IFmREREpDF8xDsREZFI4dtDSEWYiBAREYkowKkZdeHUDBEREWkMR0SIiIhECt+Pp1D8JzARISIiEink1IzaMBEhIiIS4RoR9eEaESIiItIYjogQERGJcPuu+jARISIiEuHUjPpwaoaIiIg0hiMiREREIpyaUR8mIkRERCJMRNSHUzNERESkMRwRISIiEuFiVfVhIkJERCRSyDxEbTg1Q0RERBrDEREiIiIRfteM+jARISIiEuGX76oPExEiIiIRbt9VH64RISIiIo3hiAgREZFIoYRrRNSFiQgREZEI14ioD6dmiIiISGM4IkJERCTCxarqw0SEiIhIhE9WVR9OzRAREZHGcESEiIhIhE9WVR8mIkRERCLcNaM+nJohIiIijeGICBERkQgXq6oPExEiIiIRbt9VHyYiREREIlwjoj5cI0JEREQaw0SEiIhIpFCiuqO07t27h6FDh6JKlSowMDBAkyZNcPr0aaFeoVDAx8cHVlZWMDAwgIODA65cuaLURmpqKpydnWFkZAQTExO4urri6dOnSjHnzp1Dx44doa+vD2tra/j5+b3Sl507d6J+/frQ19dHkyZNsG/fvtLf0FswESEiIhIpVOFRGo8fP0b79u1RoUIF/P3337hw4QKWLl0KU1NTIcbPzw+BgYEICgpCVFQUDA0N4ejoiOzsbCHG2dkZCQkJCAsLQ0hICCIiIjB27FihPiMjA926dUPNmjURExMDf39/zJs3D2vXrhViTpw4gSFDhsDV1RVnzpyBk5MTnJycEB8fX8q7ejOJQqEoF1NhunrVNd0FKkcy70VougtUjhjIOmq6C1TO5Ofee6ftr6s+VGVtjbn7S4ljZ8yYgePHj+Po0aPF1isUCshkMkyZMgVTp04FAKSnp8PS0hKbNm3C4MGDcfHiRTRs2BCnTp1Cq1atAAChoaHo0aMH7t69C5lMhjVr1mDWrFmQy+XQ1dUVrh0cHIxLly4BAAYNGoTMzEyEhIQI12/bti2aN2+OoKCgMv0sisMRESIiIhFVjojk5OQgIyND6cjJySn2urt370arVq0wYMAAWFhYoEWLFli3bp1Qf+PGDcjlcjg4OAhlxsbGsLOzQ2RkJAAgMjISJiYmQhICAA4ODtDS0kJUVJQQ06lTJyEJAQBHR0ckJibi8ePHQszL1ymKKbqOqjARISIiElFIVHf4+vrC2NhY6fD19S32utevX8eaNWtQp04d7N+/HxMmTMDXX3+NzZs3AwDkcjkAwNLSUuk8S0tLoU4ul8PCwkKpXkdHB2ZmZkoxxbXx8jVeF1NUryrcvktERPQOzZw5E15eXkplenp6xcYWFhaiVatW+P777wEALVq0QHx8PIKCguDi4vLO+6oJHBEhIiISUeXUjJ6eHoyMjJSO1yUiVlZWaNiwoVJZgwYNcPv2bQCAVCoFACQlJSnFJCUlCXVSqRTJyclK9fn5+UhNTVWKKa6Nl6/xupiielVhIkJERCSiqV0z7du3R2JiolLZ5cuXUbNmTQCAjY0NpFIpwsPDhfqMjAxERUXB3t4eAGBvb4+0tDTExMQIMQcPHkRhYSHs7OyEmIiICOTl5QkxYWFhqFevnrBDx97eXuk6RTFF11EVJiJERETlxOTJk3Hy5El8//33uHr1KrZt24a1a9fCzc0NACCRSODp6YmFCxdi9+7dOH/+PIYPHw6ZTAYnJycAz0dQunfvjjFjxiA6OhrHjx+Hu7s7Bg8eDJlMBgD46quvoKurC1dXVyQkJOC3335DQECA0hTSpEmTEBoaiqVLl+LSpUuYN28eTp8+DXd3d5XeM9eIEBERiWjquRatW7fGrl27MHPmTCxYsAA2NjZYvnw5nJ2dhZjp06cjMzMTY8eORVpaGjp06IDQ0FDo6+sLMVu3boW7uzu6du0KLS0t9OvXD4GBgUK9sbExDhw4ADc3N9ja2sLc3Bw+Pj5Kzxpp164dtm3bhtmzZ+Obb75BnTp1EBwcjMaNG6v0nvkcESqX+BwRehmfI0Ji7/o5IgE1VPcckUm3S/4ckQ8RR0SIiIhE+O276sM1IkRERKQxHBEhIiIS4YiI+jARISIiEikXiyc/EJyaISIiIo3hiAgREZFIoUTTPfhwMBEhIiIS4RoR9eHUDBEREWkMR0SIiIhEuFhVfZiIEBERiRQyFVGbcpOIaGtpa7oLVI7wkd70sqw7BzXdBSJ6R8pNIkJERFRecLGq+jARISIiEuHEjPowESEiIhLhiIj6cPsuERERaQxHRIiIiET4ZFX1YSJCREQkwu276sOpGSIiItIYjogQERGJcDxEfZiIEBERiXDXjPpwaoaIiIg0hiMiREREIlysqj5MRIiIiESYhqgPp2aIiIhIYzgiQkREJMLFqurDRISIiEiEa0TUh4kIERGRCNMQ9eEaESIiItIYjogQERGJcI2I+jARISIiElFwckZtODVDREREGsMRESIiIhFOzagPExEiIiIRbt9VH07NEBERkcZwRISIiEiE4yHqw0SEiIhIhFMz6sOpGSIionJo0aJFkEgk8PT0FMqys7Ph5uaGKlWqoFKlSujXrx+SkpKUzrt9+zZ69uyJihUrwsLCAtOmTUN+fr5SzOHDh9GyZUvo6emhdu3a2LRp0yvXX7VqFWrVqgV9fX3Y2dkhOjr6XdwmExEiIiKxQhUeZXHq1Cn8+OOPaNq0qVL55MmTsWfPHuzcuRNHjhzB/fv38eWXXwr1BQUF6NmzJ3Jzc3HixAls3rwZmzZtgo+PjxBz48YN9OzZE126dEFcXBw8PT0xevRo7N+/X4j57bff4OXlhblz5yI2NhbNmjWDo6MjkpOTy3hHrydRKBTlYvzJwKCmprtA5UheQf7bg+iDkXXnoKa7QOVMBct677T90bX6q6yt9Td/L1X806dP0bJlS6xevRoLFy5E8+bNsXz5cqSnp6Nq1arYtm0b+vd/3r9Lly6hQYMGiIyMRNu2bfH333+jV69euH//PiwtLQEAQUFB8Pb2xsOHD6Grqwtvb2/s3bsX8fHxwjUHDx6MtLQ0hIaGAgDs7OzQunVrrFy5EgBQWFgIa2treHh4YMaMGar4sQg4IkJERCSiyhGRnJwcZGRkKB05OTmvvbabmxt69uwJBwcHpfKYmBjk5eUpldevXx81atRAZGQkACAyMhJNmjQRkhAAcHR0REZGBhISEoQYcduOjo5CG7m5uYiJiVGK0dLSgoODgxCjSkxEiIiI3iFfX18YGxsrHb6+vsXGbt++HbGxscXWy+Vy6OrqwsTERKnc0tIScrlciHk5CSmqL6p7U0xGRgaysrKQkpKCgoKCYmOK2lAl7pohIiISUeV3zcycORNeXl5KZXp6eq/E3blzB5MmTUJYWBj09fVVdv3yjokIERGRiCof8a6np1ds4iEWExOD5ORktGzZUigrKChAREQEVq5cif379yM3NxdpaWlKoyJJSUmQSqUAAKlU+srulqJdNS/HiHfaJCUlwcjICAYGBtDW1oa2tnaxMUVtqBKnZoiIiMqBrl274vz584iLixOOVq1awdnZWfh3hQoVEB4eLpyTmJiI27dvw97eHgBgb2+P8+fPK+1uCQsLg5GRERo2bCjEvNxGUUxRG7q6urC1tVWKKSwsRHh4uBCjShwRISIiEinUwIbSypUro3HjxkplhoaGqFKlilDu6uoKLy8vmJmZwcjICB4eHrC3t0fbtm0BAN26dUPDhg0xbNgw+Pn5QS6XY/bs2XBzcxNGZcaPH4+VK1di+vTpGDVqFA4ePIgdO3Zg7969wnW9vLzg4uKCVq1aoU2bNli+fDkyMzMxcuRIld83ExEiIiKRcvFci2IsW7YMWlpa6NevH3JycuDo6IjVq1cL9dra2ggJCcGECRNgb28PQ0NDuLi4YMGCBUKMjY0N9u7di8mTJyMgIADVq1fH+vXr4ejoKMQMGjQIDx8+hI+PD+RyOZo3b47Q0NBXFrCqAp8jQuUSnyNCL+NzREjsXT9HZGjNL98eVEK/3PpTZW29jzgiQkREJMLvmlEfJiJEREQiqty+S2/GXTNERESkMRwRISIiElHlc0TozZiIEBERiXCNiPowESEiIhLhGhH14RoRIiIi0hiOiBAREYlwjYj6MBEhIiISKSfP+vwgcGqGiIiINIYjIkRERCLcNaM+TESIiIhEuEZEfTg1Q0RERBrDEREiIiIRPkdEfZiIEBERiXCNiPpwaoaIiIg0hiMiREREInyOiPowESEiIhLhrhn1YSJCREQkwsWq6sM1IiowdeoEZGXdgr+/zzu9zpw5Xrh+/RRSUxOxd+9WfPxxLaX6nTvX4/LlE3j8OBHXr5/CTz8tg5WVxTvt04fEZ44X8nPvKR3x54+8Nn74sIGvxD/NuPbO+zlhvAuuXj6JpxnXcOLYHrRu1VyoMzU1wfJl3yIhPgJP0q/i+tVoLPthAYyMKr/zfr2PTsfFw23Gt+jyxQg07tQH4UdPvvWc3Nw8BKz7GZ8NcEWLrl+i28DR+HNv2DvtZ/SZ8xjg6okWXb/E50PGIvjvcKX6VRu2oXGnPkpH76ET3mmfiIpwRORfsrVtCldXZ5w7d+FftTNrlidq1qyOsWOnFls/Zcp4TJw4AmPGTMHNm3fg4zMFe/b8jBYtHJCTkwMAiIiIhL//KsjlyZDJpPD1nYVt24LQpcuX/6pv9EJ8wiU4dh8svM7Pz39jfHp6Bho27iS8/rfzzsOHDYTL8AHo+tmAYusHDOiDJf5zMdFtBqJPncHXHqOxb+9WNGzcCQ8fPoJMZgmZzBLe3t/iwsXLqFmjOlatWgSZTIpBg8f+q759iLKyc1DvYxt80cMBnrN9S3TOlLmL8ehxGhZ4e6BGNSs8fPQYhYqyTwTce5AEx0FjEB+xu9j6u/flcPNegIF9umPRnCmIijmLuX4rULWKKdq3aSnE1bapgfU/fCu81tbWLnOf3gfcNaM+TET+BUPDiti4MQATJ3pjxgwPpTpjYyP4+s5Cr16fQU9PF7Gx5zF9+gKcP3+xTNdyc3PF4sUrERLy/JPT6NFeuHXrNPr06YadO/cAAFas+EmIv337HpYsWY0dO9ZBR0fnrX8wqWTy8wuQlPSwxPEKheKN8bq6uli4wBuDBvWFiYkxEhIuYeY33+NIRGSZ+jd50his/2kbNm/ZAQCY6DYDPT7vipEjBsPPfxUSEhIxcNCLhOP69VuY47MYWzYFQltbGwUFBWW67oeqY1tbdGxrW+L4Y1ExOH02AaHb18L4n1GoalaWr8T9HnIAm7cH4548CdWkFnDu1xuDv+hRpj7u+CsU1awsMc3dFQDwcS1rxJ6/iC07/lJKRLS1tWFexbRM13gfcbGq+nBq5l9YvvxbhIYexKFDx1+p27p1NapWrQInJxe0a9cLcXHx2LdvG0xNjUt9nVq1rGFlZYGDB48JZRkZT3DqVBzs7FoWe46pqTEGD3bCyZMxTEJUqE5tG9y+GYPLl05gy+YVsLaWvTG+UiVDXLsShRvXTuHPPzagYcO6SvWBAQvRtq0tnIdORAtbB/z+Rwj2hvyC2rVtSt23ChUqoGXLpgg/eFQoUygUCD94DG3f8MfS2KgyMjKeMglRg0PHo9GoXm1s2PYnPv1yBHp+NR7+qzYg+59RTQAIOXAYq37ahq/HDMXuLavw9ZhhWPHTVvwlmk4pqbMJl9DWtplSWfs2LXA2IVGp7Pbd++jyxQh0HzQG3guW4kEpEm6if6PUiUhWVhaOHTuGCxdenYrIzs7Gli1bVNKx8m7AgN5o3rwx5szxe6WuXbtWaNWqGZydJyI29jyuXbuJmTO/Q3p6Br4ow6caqfT5Oo/k5BSl8uTkFFhaVlUqW7hwBlJSLuL+/XOwtq6GAQNGl/p6VLzo6DMYNXoyevYeCnePmbCpVQOHD+5CpUqGxcZfvnwNo8dOwZf9R8FlhAe0tLRw9MhfqFbNCgBgbS3DCJdBGDRkHI4dj8b167fww7Ifcfz4KYxwGVTq/pmbm0FHRwfJSeLfk4eQin5PilSpYopZ33hi/U9bS309Kr279+WIPX8BV27cQsDCb+DtMRphR05g4Q9BQsyqjdswzW0kPvukHarLpPjsk3YYPqAPduzeX6ZrpqSmoYqZiVJZFVMTPM18JiRATRvWw8KZkxC0ZC7mTJmAuw+SMNx9BjKfPSvzvf7XFUKhsoPerFRTM5cvX0a3bt1w+/ZtSCQSdOjQAdu3b4eV1fM31vT0dIwcORLDhw9/Yzs5OTnCuoYiCoUCEomklN3XjOrVreDvPxe9eg195T4AoEmThqhUyRD37sUplRsY6OOjj2oCANq3b43g4M1Cna5uBUgkEqVExcPjG2zfHlyqvi1b9iM2bfoNNWpUw6xZnli/fhm+/HJkqdqg4oXuPyT8+/z5i4iKPoPrV6MwoH9vbNy0/ZX4k1ExOBkVI7w+EXka8ecOY+yYoZg7zx9NGjeAjo4OLiYcVTpPT08Xj1IfA3ierJw/e1io09HRRoUKFZCWelkoW7R4BRYtXlHq+6lcuRL2/LUFFy9exvwFS0t9PpVeYaECEkiweM4UVP4ngZ2WOwpePosx22s8CgsVuHNPDp/FKzDXf5VwXkFBASoZVhRe9x3uhvtFIxb/TCG0dhwo1Ns2bYgg/3kl7tfL00v1PrZBkwZ10W3gaIQePIZ+vbqV5Vb/87hrRn1KlYh4e3ujcePGOH36NNLS0uDp6Yn27dvj8OHDqFGjRonb8fX1xfz585XKtLWNUKGCSWm6ozEtWjSBpWVVREbuFcp0dHTQoYMdxo93wbx5/pDLk9Gt26ufatPTMwAAMTHnYGf3uVDu5jYSMpkUs2a9WPBWNAIilycDACwszIV/F70WL5J99OgxHj16jKtXbyAx8SquXo2CnV1LREXFquDO6WXp6Rm4fOU6ateuVaL4/Px8xJ1NEHY7GVYyRH5+Ptq0/fyVaZGnTzMBAPfvJ8G29Ys/BF84fY4vv+iBYS4v1iSlpqYBAFJSUpGfnw8LS3OltiwsqkIuGmavVMkQ+0K24smTTPQbMJrTd2pStYopLKqaCUkIAHxU0/r5WqLkRzA0NAAAzJvmjqaiaTwtrRcD2Gv85gr/zZJSUjHy62/wx0/LhXo9PT3h3+ZmJnj0z+9IkUeP01DJsCL0X4p7mVHlSqhpLcPtew/KdJ9EpVGqROTEiRP43//+B3Nzc5ibm2PPnj2YOHEiOnbsiEOHDsHQsPgharGZM2fCy8tLqczConFpuqJRhw4dh63tZ0pla9cuQWLiNSxdugZSqQUsLasiP78At2/fLbaN7OwcXL9+S3idmpqGypUrKZUVuXnzDh48SEaXLu2FxKNy5Upo3bo51q375bX9LHrj0tXVLfU90tsZGlbExx/VxNatf5QoXktLC40b10fo3wcBAHFx8dDR0YFF1So4djy62HMKCgpw7dpN4XVy8iNkZWUrlRXJy8tDbOw5fNqlA3b/M4wvkUjwaZcOWL1moxBXuXIl/L13G3JycuD05YhiR/Xo3WjRpAEOHD6OZ8+yULHi86Tj1p170NLSgqVFFejr6cHC3Ax3H8jRq1vn17Yjk77Yll+0u6VG9eLXKzVrVB9HT8YolUWejkOzRvVe2/6zZ1m4c0+O3t26lPTW3juFXKyqNqVKRLKysqCj8+IUiUSCNWvWwN3dHZ988gm2bdtWonb09PSUMvaitv4rnj7NxIULl5XKMjOfITX1MS5cuIwLFy4jKioWO3asxaxZvrhy5QZkMkt07/4pdu8ORWzs+VJfc9Wqn+Dt7YGrV2/g5s07mDt3Ch48SMbu3QcAAK1bN4etbTOcOHEKaWnpsLGpiblzp+DatZscDVERv0VzELI3DLdu34XMSoq5PlNQUFCI7b8FAwA2bgjA/fsPMGv2IgDA7FmeiIqKxdVrN2FibIQpUyagZo1q+Gnj8/9Prly5jq3b/sDGDQGY5r0AcXHxqGpeBZ9+2gHnz1/EvjIsTlwWsA4bf1qGmNhzOHXqDL72GANDQwNs2vwbgOdJSOi+X2FQUR/DR3jAyKiy8AyRhw8fobCQz5MsjWfPspRGDe49SMKlK9dhbFQZVpZVsezHzUhOSYXvrMkAgJ4OnyBo8w7MXhQAt1Ff4XFaBpau2YQvejgIoxMTR32FRQFrUcnQEB3sWiI3Nw8JiVeR8eQpXAY5lbqPA/t2x6+79mLpmo34osdniI49h/2HjmH14hfPPfJftQGd27eBzLIqklNSsWrjNmhraaGHQ6c3tPx+YxqiPqVKROrXr4/Tp0+jQYMGSuUrV64EAPTp00d1PfuPc3Iagfnzp2Ht2iUwNzdDUtJDHDsW/cqC05JaujQIFStWxMqVvjAxMcKJE6fRp89w4dPss2dZ6Nu3O2bPngxDQwPI5Q9x4MBhLF68Arm5uaq8tQ9WtepW+OXnVahSxRQPH6bi+IlotO/YGykpqQCAGtYypT/kpiYmCFrjD6m0Kh4/Tkds7Hl0/KQvLl68IsS4jvbCrG8mwX+xD6pVkyIlJRVR0bHYu+9/Zerjzp27UdXcDPN8pkIqrYqzZxPQs9dQ4feuZYsmwk6ry5dOKJ37cR073LpV/AgeFS8+8SpGTZolvPZb+XwLfd/un+K7bzyR8uix0u6TihUNsO6HBfg+4EcMGuMFYyMjdO/SHh5jhgox/Xt1g4GeHjZu/xNL12yEgb4+6n5UE0MHlO39tbpMilWLfeC3cj1++X0PLKuaY/50D6Wtu0kPH2H6/CVIy8iAmYkxWjRpiK1B/jAzKf0uP6LSkihKsVna19cXR48exb59+4qtnzhxIoKCgsr0qcrAoGapz6H3V14B1yzQC1l3Dmq6C1TOVLB8/dSSKrSv9qnK2jp+j7+/b1KqRORdYiJCL2MiQi9jIkJi7zoRsa+muvUxkfcOvT3oA8YnqxIREYmUk8/oHwQ+WZWIiIg0hiMiREREInwiqvowESEiIhLhk1XVh1MzREREpDFMRIiIiEQUCoXKjtLw9fVF69atUblyZVhYWMDJyQmJicrflJydnQ03NzdUqVIFlSpVQr9+/ZCUlKQUc/v2bfTs2RMVK1aEhYUFpk2b9spXORw+fBgtW7aEnp4eateujU2bNr3Sn1WrVqFWrVrQ19eHnZ0doqOLfwr0v8FEhIiISERT37575MgRuLm54eTJkwgLC0NeXh66deuGzMxMIWby5MnYs2cPdu7ciSNHjuD+/fv48ssvhfqCggL07NkTubm5OHHiBDZv3oxNmzbBx+fF03Rv3LiBnj17okuXLoiLi4OnpydGjx6N/ftffMvzb7/9Bi8vL8ydOxexsbFo1qwZHB0dkZz84jvPVIHPEaFyic8RoZfxOSIk9q6fI9LSqoPK2op9cKzM5z58+BAWFhY4cuQIOnXqhPT0dFStWhXbtm1D//79AQCXLl1CgwYNEBkZibZt2+Lvv/9Gr169cP/+fVhaWgIAgoKC4O3tjYcPH0JXVxfe3t7Yu3cv4uPjhWsNHjwYaWlpCA0NBQDY2dmhdevWwtPTCwsLYW1tDQ8PD8yYMaPM9yTGEREiIiIRVU7N5OTkICMjQ+ko6ZdNpqenAwDMzMwAADExMcjLy4ODg4MQU79+fdSoUQORkZEAgMjISDRp0kRIQgDA0dERGRkZSEhIEGJebqMopqiN3NxcxMTEKMVoaWnBwcFBiFEVJiJEREQiqpya8fX1hbGxsdLh6+v79j4UFsLT0xPt27dH48bPv6FeLpdDV1cXJiYmSrGWlpaQy+VCzMtJSFF9Ud2bYjIyMpCVlYWUlBQUFBQUG1PUhqpw+y4REdE7NHPmTHh5eSmVib+Bvjhubm6Ij4/HsWNln9r5L2AiQkREJKLK54jo6emVKPF4mbu7O0JCQhAREYHq1asL5VKpFLm5uUhLS1MaFUlKSoJUKhVixLtbinbVvBwj3mmTlJQEIyMjGBgYQFtbG9ra2sXGFLWhKpyaISIiEilUKFR2lIZCoYC7uzt27dqFgwcPwsbGRqne1tYWFSpUQHh4uFCWmJiI27dvw97eHgBgb2+P8+fPK+1uCQsLg5GRERo2bCjEvNxGUUxRG7q6urC1tVWKKSwsRHh4uBCjKhwRISIiEtHUk1Xd3Nywbds2/PXXX6hcubKwHsPY2BgGBgYwNjaGq6srvLy8YGZmBiMjI3h4eMDe3h5t27YFAHTr1g0NGzbEsGHD4OfnB7lcjtmzZ8PNzU0YmRk/fjxWrlyJ6dOnY9SoUTh48CB27NiBvXv3Cn3x8vKCi4sLWrVqhTZt2mD58uXIzMzEyJEjVXrP3L5L5RK379LLuH2XxN719t1GlnYqayshKarEsRKJpNjyjRs3YsSIEQCeP9BsypQp+PXXX5GTkwNHR0esXr1aacrk1q1bmDBhAg4fPgxDQ0O4uLhg0aJF0NF5Mf5w+PBhTJ48GRcuXED16tUxZ84c4RpFVq5cCX9/f8jlcjRv3hyBgYGws1PdzwZgIkLlFBMRehkTERJ714lIA4s2KmvrYrLqn0b6PuHUDBERkQi/9E59uFiViIiINIYjIkRERCKl3e1CZcdEhIiISIRTM+rDqRkiIiLSGI6IEBERiXBqRn2YiBAREYlwakZ9ODVDREREGsMRESIiIhGFolDTXfhgMBEhIiISKeTUjNowESEiIhIpJ99+8kHgGhEiIiLSGI6IEBERiXBqRn2YiBAREYlwakZ9ODVDREREGsMRESIiIhE+WVV9mIgQERGJ8Mmq6sOpGSIiItIYjogQERGJcLGq+jARISIiEuH2XfXh1AwRERFpDEdEiIiIRDg1oz5MRIiIiES4fVd9mIgQERGJcEREfbhGhIiIiDSGIyJEREQi3DWjPkxEiIiIRDg1oz6cmiEiIiKN4YgIERGRCHfNqA8TESIiIhF+6Z36cGqGiIiINIYjIkRERCKcmlEfJiJEREQi3DWjPpyaISIiIo3hiAgREZEIF6uqDxMRIiIiEU7NqA8TESIiIhEmIurDNSJERESkMRwRISIiEuF4iPpIFBx/KjdycnLg6+uLmTNnQk9PT9PdIQ3j7wO9jL8P9L5iIlKOZGRkwNjYGOnp6TAyMtJ0d0jD+PtAL+PvA72vuEaEiIiINIaJCBEREWkMExEiIiLSGCYi5Yienh7mzp3LhWgEgL8PpIy/D/S+4mJVIiIi0hiOiBAREZHGMBEhIiIijWEiQkRERBrDRISIiIg0holIObFq1SrUqlUL+vr6sLOzQ3R0tKa7RBoSERGB3r17QyaTQSKRIDg4WNNdIg3y9fVF69atUblyZVhYWMDJyQmJiYma7haRyjARKQd+++03eHl5Ye7cuYiNjUWzZs3g6OiI5ORkTXeNNCAzMxPNmjXDqlWrNN0VKgeOHDkCNzc3nDx5EmFhYcjLy0O3bt2QmZmp6a4RqQS375YDdnZ2aN26NVauXAkAKCwshLW1NTw8PDBjxgwN9440SSKRYNeuXXByctJ0V6icePjwISwsLHDkyBF06tRJ090h+tc4IqJhubm5iImJgYODg1CmpaUFBwcHREZGarBnRFQepaenAwDMzMw03BMi1WAiomEpKSkoKCiApaWlUrmlpSXkcrmGekVE5VFhYSE8PT3Rvn17NG7cWNPdIVIJHU13gIiISsbNzQ3x8fE4duyYprtCpDJMRDTM3Nwc2traSEpKUipPSkqCVCrVUK+IqLxxd3dHSEgIIiIiUL16dU13h0hlODWjYbq6urC1tUV4eLhQVlhYiPDwcNjb22uwZ0RUHigUCri7u2PXrl04ePAgbGxsNN0lIpXiiEg54OXlBRcXF7Rq1Qpt2rTB8uXLkZmZiZEjR2q6a6QBT58+xdWrV4XXN27cQFxcHMzMzFCjRg0N9ow0wc3NDdu2bcNff/2FypUrC2vHjI2NYWBgoOHeEf173L5bTqxcuRL+/v6Qy+Vo3rw5AgMDYWdnp+lukQYcPnwYXbp0eaXcxcUFmzZtUn+HSKMkEkmx5Rs3bsSIESPU2xmid4CJCBEREWkM14gQERGRxjARISIiIo1hIkJEREQaw0SEiIiINIaJCBEREWkMExEiIiLSGCYiREREpDFMRIiIiEhjmIgQERGRxjARISIiIo1hIkJEREQaw0SEiIiINOb/PVa/YmYarZEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Heatmap 시각화 (confusion matrix 시각화하기)\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "cm = confusion_matrix(y_test, predict_test)\n",
    "\n",
    "# 혼동 행렬을 DataFrame으로 변환\n",
    "cm_df = pd.DataFrame(cm, columns=y.unique(), index=y.unique())\n",
    "\n",
    "sns.heatmap(cm, annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70948ca5",
   "metadata": {},
   "source": [
    "## 2만개로 출발 데이터 줄이기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b18222a5-0834-4551-a8d1-967c3a33fd7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "출발       20000\n",
      "기상 지연     4918\n",
      "기상 취소      473\n",
      "Name: 현황, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 데이터프레임에서 \"출발\"인 값을 가진 행을 추출\n",
    "selected_data = df[df['현황'] == \"출발\"]\n",
    "\n",
    "# 랜덤하게 20,000개 추출\n",
    "random_selected_data = selected_data.sample(n=20000, random_state=42)\n",
    "\n",
    "# 지연 데이터 와 취소 데이터 추출하기\n",
    "delay_data = df[df['현황'] == \"기상 지연\"]\n",
    "cancel_data = df[df['현황'] == '기상 취소']\n",
    "\n",
    "new = [random_selected_data, delay_data, cancel_data]\n",
    "\n",
    "# 데이터프레임들을 수직 방향으로 합치기\n",
    "new_df = pd.concat(new, axis=0, ignore_index=True)\n",
    "new_df\n",
    "print(new_df['현황'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1afc3b0c",
   "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>날짜</th>\n",
       "      <th>항공사</th>\n",
       "      <th>편명</th>\n",
       "      <th>출발공항코드</th>\n",
       "      <th>출발공항명</th>\n",
       "      <th>도착공항코드</th>\n",
       "      <th>도착공항명</th>\n",
       "      <th>계획시간</th>\n",
       "      <th>예상시간</th>\n",
       "      <th>출발시간</th>\n",
       "      <th>시간</th>\n",
       "      <th>온도</th>\n",
       "      <th>시정</th>\n",
       "      <th>전운량</th>\n",
       "      <th>최저운고</th>\n",
       "      <th>풍속</th>\n",
       "      <th>강수량(mm)</th>\n",
       "      <th>구분</th>\n",
       "      <th>현황</th>\n",
       "      <th>사유</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-10-09 00:00:00</td>\n",
       "      <td>아시아나항공</td>\n",
       "      <td>OZ122</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>NGO</td>\n",
       "      <td>나고야</td>\n",
       "      <td>08:15</td>\n",
       "      <td>08:15</td>\n",
       "      <td>08:25</td>\n",
       "      <td>08:00</td>\n",
       "      <td>13.1</td>\n",
       "      <td>1000</td>\n",
       "      <td>7</td>\n",
       "      <td>120.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-11-10 00:00:00</td>\n",
       "      <td>아시아나항공</td>\n",
       "      <td>OZ309</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>WEH</td>\n",
       "      <td>위해</td>\n",
       "      <td>09:00</td>\n",
       "      <td>09:00</td>\n",
       "      <td>09:44</td>\n",
       "      <td>09:00</td>\n",
       "      <td>14.0</td>\n",
       "      <td>350</td>\n",
       "      <td>2</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-07-09 00:00:00</td>\n",
       "      <td>독일항공</td>\n",
       "      <td>LH719</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>MUC</td>\n",
       "      <td>뮌헨</td>\n",
       "      <td>12:15</td>\n",
       "      <td>12:15</td>\n",
       "      <td>12:36</td>\n",
       "      <td>12:00</td>\n",
       "      <td>28.4</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-10-01 00:00:00</td>\n",
       "      <td>필리핀항공</td>\n",
       "      <td>PR485</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>CEB</td>\n",
       "      <td>세부</td>\n",
       "      <td>08:30</td>\n",
       "      <td>08:30</td>\n",
       "      <td>08:41</td>\n",
       "      <td>08:00</td>\n",
       "      <td>17.2</td>\n",
       "      <td>1000</td>\n",
       "      <td>4</td>\n",
       "      <td>40.0</td>\n",
       "      <td>16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-12-29 00:00:00</td>\n",
       "      <td>제주항공</td>\n",
       "      <td>7C1404</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>FUK</td>\n",
       "      <td>후쿠오카</td>\n",
       "      <td>15:30</td>\n",
       "      <td>15:30</td>\n",
       "      <td>15:50</td>\n",
       "      <td>15:00</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>출발</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25386</th>\n",
       "      <td>2019-12-02 00:00:00</td>\n",
       "      <td>진에어</td>\n",
       "      <td>LJ023</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>CRK</td>\n",
       "      <td>클라크 국제공항</td>\n",
       "      <td>21:35</td>\n",
       "      <td>:</td>\n",
       "      <td>:</td>\n",
       "      <td>21:00</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>기상 취소</td>\n",
       "      <td>태풍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25387</th>\n",
       "      <td>2019-12-09 00:00:00</td>\n",
       "      <td>산동항공</td>\n",
       "      <td>SC4988</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>TNA</td>\n",
       "      <td>지난</td>\n",
       "      <td>22:05</td>\n",
       "      <td>:</td>\n",
       "      <td>:</td>\n",
       "      <td>22:00</td>\n",
       "      <td>8.8</td>\n",
       "      <td>600</td>\n",
       "      <td>8</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>기상 취소</td>\n",
       "      <td>시정</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25388</th>\n",
       "      <td>2019-12-10 00:00:00</td>\n",
       "      <td>산동항공</td>\n",
       "      <td>SC4988</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>TNA</td>\n",
       "      <td>지난</td>\n",
       "      <td>22:05</td>\n",
       "      <td>22:05</td>\n",
       "      <td>:</td>\n",
       "      <td>22:00</td>\n",
       "      <td>8.6</td>\n",
       "      <td>180</td>\n",
       "      <td>6</td>\n",
       "      <td>20.0</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>기상 취소</td>\n",
       "      <td>시정</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25389</th>\n",
       "      <td>2019-12-09 00:00:00</td>\n",
       "      <td>산동항공</td>\n",
       "      <td>SC4722</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>TAO</td>\n",
       "      <td>청도</td>\n",
       "      <td>23:50</td>\n",
       "      <td>:</td>\n",
       "      <td>:</td>\n",
       "      <td>23:00</td>\n",
       "      <td>9.8</td>\n",
       "      <td>600</td>\n",
       "      <td>8</td>\n",
       "      <td>20.0</td>\n",
       "      <td>13</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>기상 취소</td>\n",
       "      <td>시정</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25390</th>\n",
       "      <td>2019-12-16 00:00:00</td>\n",
       "      <td>중국동방항공</td>\n",
       "      <td>MU5086</td>\n",
       "      <td>ICN</td>\n",
       "      <td>인천</td>\n",
       "      <td>YNJ</td>\n",
       "      <td>연길</td>\n",
       "      <td>23:10</td>\n",
       "      <td>23:10</td>\n",
       "      <td>:</td>\n",
       "      <td>23:00</td>\n",
       "      <td>9.6</td>\n",
       "      <td>800</td>\n",
       "      <td>8</td>\n",
       "      <td>40.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>여객</td>\n",
       "      <td>기상 취소</td>\n",
       "      <td>강수(눈)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25391 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        날짜     항공사      편명 출발공항코드 출발공항명 도착공항코드     도착공항명  \\\n",
       "0      2018-10-09 00:00:00  아시아나항공   OZ122    ICN    인천    NGO       나고야   \n",
       "1      2018-11-10 00:00:00  아시아나항공   OZ309    ICN    인천    WEH        위해   \n",
       "2      2017-07-09 00:00:00    독일항공   LH719    ICN    인천    MUC        뮌헨   \n",
       "3      2018-10-01 00:00:00   필리핀항공   PR485    ICN    인천    CEB        세부   \n",
       "4      2018-12-29 00:00:00    제주항공  7C1404    ICN    인천    FUK      후쿠오카   \n",
       "...                    ...     ...     ...    ...   ...    ...       ...   \n",
       "25386  2019-12-02 00:00:00     진에어   LJ023    ICN    인천    CRK  클라크 국제공항   \n",
       "25387  2019-12-09 00:00:00    산동항공  SC4988    ICN    인천    TNA        지난   \n",
       "25388  2019-12-10 00:00:00    산동항공  SC4988    ICN    인천    TNA        지난   \n",
       "25389  2019-12-09 00:00:00    산동항공  SC4722    ICN    인천    TAO        청도   \n",
       "25390  2019-12-16 00:00:00  중국동방항공  MU5086    ICN    인천    YNJ        연길   \n",
       "\n",
       "        계획시간   예상시간   출발시간     시간    온도    시정  전운량   최저운고  풍속  강수량(mm)  구분  \\\n",
       "0      08:15  08:15  08:25  08:00  13.1  1000    7  120.0   7      0.0  여객   \n",
       "1      09:00  09:00  09:44  09:00  14.0   350    2   20.0   7      0.0  여객   \n",
       "2      12:15  12:15  12:36  12:00  28.4  1000    8   10.0  10      0.0  여객   \n",
       "3      08:30  08:30  08:41  08:00  17.2  1000    4   40.0  16      0.0  여객   \n",
       "4      15:30  15:30  15:50  15:00  -4.0  1000    0    0.0  10      0.0  여객   \n",
       "...      ...    ...    ...    ...   ...   ...  ...    ...  ..      ...  ..   \n",
       "25386  21:35      :      :  21:00  -1.3  1000    8   30.0   3      0.0  여객   \n",
       "25387  22:05      :      :  22:00   8.8   600    8   20.0  16      0.0  여객   \n",
       "25388  22:05  22:05      :  22:00   8.6   180    6   20.0  11      0.0  여객   \n",
       "25389  23:50      :      :  23:00   9.8   600    8   20.0  13      0.0  여객   \n",
       "25390  23:10  23:10      :  23:00   9.6   800    8   40.0   9      0.0  여객   \n",
       "\n",
       "          현황     사유  \n",
       "0         출발    NaN  \n",
       "1         출발    NaN  \n",
       "2         출발    NaN  \n",
       "3         출발    NaN  \n",
       "4         출발    NaN  \n",
       "...      ...    ...  \n",
       "25386  기상 취소     태풍  \n",
       "25387  기상 취소     시정  \n",
       "25388  기상 취소     시정  \n",
       "25389  기상 취소     시정  \n",
       "25390  기상 취소  강수(눈)  \n",
       "\n",
       "[25391 rows x 20 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "261d6c29",
   "metadata": {},
   "source": [
    "### 2만개 데이터 증폭 전 분포"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "692acd91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 사용할 칼럼들을 추출 (기상 요건들과 운송 현황)\n",
    "selected = ['온도','시정', '전운량', '최저운고','풍속', '강수량(mm)', '현황']\n",
    "sdf3 = new_df[selected]\n",
    "\n",
    "sns.scatterplot(data=sdf3, x=sdf3.iloc[:, 0], y=sdf3.iloc[:, 1], hue='현황')\n",
    "plt.title(\"2만개 데이터 증폭 전 분포\")\n",
    "plt.savefig('/Users/user/Documents/DataMining/termproject.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fb667ca8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counter({'출발': 20000, '기상 지연': 4918, '기상 취소': 473})\n"
     ]
    }
   ],
   "source": [
    "new_X = new_df[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "new_y = new_df['현황']\n",
    "from collections import Counter  \n",
    "counter2 = Counter(new_y)\n",
    "print(counter2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16b76e4e",
   "metadata": {},
   "source": [
    "## 2만개 데이터 SMOTE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fbff235d-361e-4144-8940-675ef0bab64e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "원본 데이터셋의 각 카테고리별 개수:\n",
      "출발       20000\n",
      "기상 지연     4918\n",
      "기상 취소      473\n",
      "Name: 현황, dtype: int64\n",
      "Counter({'출발': 20000, '기상 지연': 20000, '기상 취소': 20000})\n",
      "\n",
      "새로운 데이터셋의 각 카테고리별 개수:\n",
      "출발       20000\n",
      "기상 지연    20000\n",
      "기상 취소    20000\n",
      "Name: 현황, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 각 카테고리별 데이터 개수 출력\n",
    "print(\"원본 데이터셋의 각 카테고리별 개수:\")\n",
    "print(new_df['현황'].value_counts())\n",
    "\n",
    "# 출발 이외의 데이터를 추출\n",
    "non_departure_data2 = new_df[new_df['현황'] != '출발']\n",
    "\n",
    "# 출발 데이터만 따로 추출\n",
    "departure_data2 = new_df[new_df['현황'] == '출발']\n",
    "\n",
    "# 각 카테고리별 데이터 개수에 맞게 샘플링\n",
    "from imblearn.over_sampling import SMOTE\n",
    "smt2 = SMOTE(sampling_strategy='auto',random_state=42)\n",
    "\n",
    "# 데이터 증강\n",
    "X_sm2, y_sm2 = smt2.fit_resample(new_X,new_y)\n",
    "\n",
    "#클래스 수 파악 \n",
    "from collections import Counter  \n",
    "counter2 = Counter(y_sm2)\n",
    "print(counter2)\n",
    "\n",
    "# # dataframe 연결\n",
    "X_sm2 = pd.DataFrame(X_sm2)\n",
    "y_sm2 = pd.DataFrame(y_sm2)\n",
    "smote_data2 = pd.concat([X_sm2, y_sm2], axis=1)\n",
    "\n",
    "# 새로운 데이터셋의 각 카테고리별 개수 출력\n",
    "print(\"\\n새로운 데이터셋의 각 카테고리별 개수:\")\n",
    "print(smote_data2['현황'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9f1d3c0a-443e-43ad-913a-1183f6198a7e",
   "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>온도</th>\n",
       "      <th>시정</th>\n",
       "      <th>전운량</th>\n",
       "      <th>최저운고</th>\n",
       "      <th>풍속</th>\n",
       "      <th>강수량(mm)</th>\n",
       "      <th>현황</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13.100000</td>\n",
       "      <td>1000</td>\n",
       "      <td>7</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14.000000</td>\n",
       "      <td>350</td>\n",
       "      <td>2</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28.400000</td>\n",
       "      <td>1000</td>\n",
       "      <td>8</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17.200000</td>\n",
       "      <td>1000</td>\n",
       "      <td>4</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>16</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>출발</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-4.000000</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>출발</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59995</th>\n",
       "      <td>25.795194</td>\n",
       "      <td>1000</td>\n",
       "      <td>7</td>\n",
       "      <td>14.759694</td>\n",
       "      <td>9</td>\n",
       "      <td>0.096122</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59996</th>\n",
       "      <td>22.236310</td>\n",
       "      <td>1000</td>\n",
       "      <td>7</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>9</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59997</th>\n",
       "      <td>23.200000</td>\n",
       "      <td>200</td>\n",
       "      <td>8</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>28</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59998</th>\n",
       "      <td>35.000000</td>\n",
       "      <td>1000</td>\n",
       "      <td>3</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>17</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59999</th>\n",
       "      <td>25.554305</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>기상 취소</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>60000 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              온도    시정  전운량        최저운고  풍속   강수량(mm)     현황\n",
       "0      13.100000  1000    7  120.000000   7  0.000000     출발\n",
       "1      14.000000   350    2   20.000000   7  0.000000     출발\n",
       "2      28.400000  1000    8   10.000000  10  0.000000     출발\n",
       "3      17.200000  1000    4   40.000000  16  0.000000     출발\n",
       "4      -4.000000  1000    0    0.000000  10  0.000000     출발\n",
       "...          ...   ...  ...         ...  ..       ...    ...\n",
       "59995  25.795194  1000    7   14.759694   9  0.096122  기상 취소\n",
       "59996  22.236310  1000    7   30.000000   9  0.000000  기상 취소\n",
       "59997  23.200000   200    8    5.000000  28  0.000000  기상 취소\n",
       "59998  35.000000  1000    3   50.000000  17  0.000000  기상 취소\n",
       "59999  25.554305  1000    0    0.000000  10  0.000000  기상 취소\n",
       "\n",
       "[60000 rows x 7 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smote_data2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c14caf4",
   "metadata": {},
   "source": [
    "### 2만개 데이터 증폭 후 분포 (SMOTE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2615888f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 사용할 칼럼들을 추출 (기상 요건들과 운송 현황)\n",
    "selected = ['온도','시정', '전운량', '최저운고','풍속', '강수량(mm)', '현황']\n",
    "sdf4 = smote_data2[selected]\n",
    "\n",
    "sns.scatterplot(data=sdf4, x=sdf4.iloc[:, 0], y=sdf4.iloc[:, 1], hue='현황')\n",
    "plt.title(\"2만개 데이터 SMOTE 증폭 후 분포\")\n",
    "plt.savefig('/Users/user/Documents/DataMining/termproject.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c304b8bf-66cd-450e-adbd-5f6699485f38",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(17773, 6) (7618, 6) (17773,) (7618,)\n"
     ]
    }
   ],
   "source": [
    "#test, training (7:3 분할)\n",
    "X_train2, X_test2, y_train2, y_test2 = train_test_split(new_X,new_y,test_size = 0.3, random_state = 100)\n",
    "print(X_train2.shape, X_test2.shape, y_train2.shape, y_test2.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f2ad1f7-1533-4409-8c52-ac5f049ab013",
   "metadata": {},
   "source": [
    "# 4. 모델링 - Decision Tree (2만개 SMOTE Data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c605a2b1",
   "metadata": {},
   "source": [
    "### Hyper Parameter Tuning - GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4b8ab4a8-049d-4483-a2c8-e2423958d29d",
   "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>max_depth</th>\n",
       "      <th>min_samples_split</th>\n",
       "      <th>splitter</th>\n",
       "      <th>mean_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.877343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.877061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.875879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.874867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.873685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.873629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.873179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>25</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.872897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.872729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.872448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>20</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.872054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>30</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.871828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>25</td>\n",
       "      <td>64</td>\n",
       "      <td>best</td>\n",
       "      <td>0.871772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>20</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.871603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td>128</td>\n",
       "      <td>best</td>\n",
       "      <td>0.871547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>20</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.871097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.870703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>25</td>\n",
       "      <td>32</td>\n",
       "      <td>best</td>\n",
       "      <td>0.870647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>15</td>\n",
       "      <td>128</td>\n",
       "      <td>best</td>\n",
       "      <td>0.870590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>25</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.870422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>30</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.870141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>20</td>\n",
       "      <td>128</td>\n",
       "      <td>best</td>\n",
       "      <td>0.870084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>30</td>\n",
       "      <td>128</td>\n",
       "      <td>best</td>\n",
       "      <td>0.870028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>25</td>\n",
       "      <td>128</td>\n",
       "      <td>best</td>\n",
       "      <td>0.870028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.869971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>30</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.869521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>25</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.869465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>random</td>\n",
       "      <td>0.867608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>20</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.867383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>15</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.866933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.866765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10</td>\n",
       "      <td>256</td>\n",
       "      <td>best</td>\n",
       "      <td>0.866314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>15</td>\n",
       "      <td>256</td>\n",
       "      <td>best</td>\n",
       "      <td>0.865977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>30</td>\n",
       "      <td>256</td>\n",
       "      <td>best</td>\n",
       "      <td>0.865864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>20</td>\n",
       "      <td>256</td>\n",
       "      <td>best</td>\n",
       "      <td>0.865864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>25</td>\n",
       "      <td>256</td>\n",
       "      <td>best</td>\n",
       "      <td>0.865864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>25</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.865246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>30</td>\n",
       "      <td>16</td>\n",
       "      <td>best</td>\n",
       "      <td>0.865134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>32</td>\n",
       "      <td>random</td>\n",
       "      <td>0.863783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>64</td>\n",
       "      <td>random</td>\n",
       "      <td>0.863219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>15</td>\n",
       "      <td>128</td>\n",
       "      <td>random</td>\n",
       "      <td>0.862094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>512</td>\n",
       "      <td>best</td>\n",
       "      <td>0.860744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>30</td>\n",
       "      <td>512</td>\n",
       "      <td>best</td>\n",
       "      <td>0.860744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>25</td>\n",
       "      <td>512</td>\n",
       "      <td>best</td>\n",
       "      <td>0.860744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>15</td>\n",
       "      <td>512</td>\n",
       "      <td>best</td>\n",
       "      <td>0.860744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>20</td>\n",
       "      <td>512</td>\n",
       "      <td>best</td>\n",
       "      <td>0.860744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>25</td>\n",
       "      <td>128</td>\n",
       "      <td>random</td>\n",
       "      <td>0.860407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>30</td>\n",
       "      <td>128</td>\n",
       "      <td>random</td>\n",
       "      <td>0.860407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>128</td>\n",
       "      <td>random</td>\n",
       "      <td>0.859787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>20</td>\n",
       "      <td>128</td>\n",
       "      <td>random</td>\n",
       "      <td>0.859675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>25</td>\n",
       "      <td>256</td>\n",
       "      <td>random</td>\n",
       "      <td>0.855568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>30</td>\n",
       "      <td>256</td>\n",
       "      <td>random</td>\n",
       "      <td>0.855568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>256</td>\n",
       "      <td>random</td>\n",
       "      <td>0.855342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>15</td>\n",
       "      <td>256</td>\n",
       "      <td>random</td>\n",
       "      <td>0.855286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>20</td>\n",
       "      <td>256</td>\n",
       "      <td>random</td>\n",
       "      <td>0.854893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>25</td>\n",
       "      <td>512</td>\n",
       "      <td>random</td>\n",
       "      <td>0.853260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>15</td>\n",
       "      <td>512</td>\n",
       "      <td>random</td>\n",
       "      <td>0.853260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>20</td>\n",
       "      <td>512</td>\n",
       "      <td>random</td>\n",
       "      <td>0.853260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>30</td>\n",
       "      <td>512</td>\n",
       "      <td>random</td>\n",
       "      <td>0.853260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10</td>\n",
       "      <td>512</td>\n",
       "      <td>random</td>\n",
       "      <td>0.847521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    max_depth  min_samples_split splitter  mean_test_score\n",
       "0          10                 16     best         0.877343\n",
       "2          10                 32     best         0.877061\n",
       "4          10                 64     best         0.875879\n",
       "13         15                 16   random         0.874867\n",
       "25         20                 16   random         0.873685\n",
       "14         15                 32     best         0.873629\n",
       "16         15                 64     best         0.873179\n",
       "39         25                 32   random         0.872897\n",
       "51         30                 32   random         0.872729\n",
       "12         15                 16     best         0.872448\n",
       "28         20                 64     best         0.872054\n",
       "52         30                 64     best         0.871828\n",
       "40         25                 64     best         0.871772\n",
       "27         20                 32   random         0.871603\n",
       "6          10                128     best         0.871547\n",
       "26         20                 32     best         0.871097\n",
       "50         30                 32     best         0.870703\n",
       "38         25                 32     best         0.870647\n",
       "18         15                128     best         0.870590\n",
       "37         25                 16   random         0.870422\n",
       "49         30                 16   random         0.870141\n",
       "30         20                128     best         0.870084\n",
       "54         30                128     best         0.870028\n",
       "42         25                128     best         0.870028\n",
       "15         15                 32   random         0.869971\n",
       "53         30                 64   random         0.869521\n",
       "41         25                 64   random         0.869465\n",
       "1          10                 16   random         0.867608\n",
       "29         20                 64   random         0.867383\n",
       "17         15                 64   random         0.866933\n",
       "24         20                 16     best         0.866765\n",
       "8          10                256     best         0.866314\n",
       "20         15                256     best         0.865977\n",
       "56         30                256     best         0.865864\n",
       "32         20                256     best         0.865864\n",
       "44         25                256     best         0.865864\n",
       "36         25                 16     best         0.865246\n",
       "48         30                 16     best         0.865134\n",
       "3          10                 32   random         0.863783\n",
       "5          10                 64   random         0.863219\n",
       "19         15                128   random         0.862094\n",
       "10         10                512     best         0.860744\n",
       "58         30                512     best         0.860744\n",
       "46         25                512     best         0.860744\n",
       "22         15                512     best         0.860744\n",
       "34         20                512     best         0.860744\n",
       "43         25                128   random         0.860407\n",
       "55         30                128   random         0.860407\n",
       "7          10                128   random         0.859787\n",
       "31         20                128   random         0.859675\n",
       "45         25                256   random         0.855568\n",
       "57         30                256   random         0.855568\n",
       "9          10                256   random         0.855342\n",
       "21         15                256   random         0.855286\n",
       "33         20                256   random         0.854893\n",
       "47         25                512   random         0.853260\n",
       "23         15                512   random         0.853260\n",
       "35         20                512   random         0.853260\n",
       "59         30                512   random         0.853260\n",
       "11         10                512   random         0.847521"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "#테스트하고자 하는 파라미터 값들을 사전 타입으로 정의\n",
    "dt_clf2 = DecisionTreeClassifier(random_state = 33)\n",
    "parameters = {'max_depth': [10, 15, 20, 25, 30],\n",
    "              'min_samples_split': [16, 32, 64, 128, 256, 512],\n",
    "              'splitter': ['best', 'random']}\n",
    "\n",
    "grid_dt2 = GridSearchCV(dt_clf2, # estimator 객체,\n",
    "                      param_grid = parameters, cv = 5\n",
    "                      # n_jobs = -1: 모든 cpu를 사용)\n",
    "                      )\n",
    "\n",
    "grid_dt2.fit(X_train2, y_train2)\n",
    "\n",
    "result2 = pd.DataFrame(grid_dt2.cv_results_['params'])\n",
    "result2['mean_test_score'] = grid_dt2.cv_results_['mean_test_score']\n",
    "result2.sort_values(by='mean_test_score', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "022c1ef0-4025-4a46-bdc0-10c07bc93bbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {color: black;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=30, min_samples_split=16)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeClassifier</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeClassifier(max_depth=30, min_samples_split=16)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeClassifier(max_depth=30, min_samples_split=16)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_params = {'max_depth' : 30, 'min_samples_split': 16, 'splitter': 'best'}\n",
    "\n",
    "#최적 파라미터 조합으로 DecisionTreeClassifier 초기화\n",
    "best_dt2 = DecisionTreeClassifier(**best_params)\n",
    "\n",
    "#최적모델로 학습\n",
    "best_dt2.fit(X_train2, y_train2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4a5f0ff",
   "metadata": {},
   "source": [
    "### 교차검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "de0669c5-5532-41c5-945c-5bdce61b0300",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차검증 평균:  0.8065848138211067\n"
     ]
    }
   ],
   "source": [
    "#교차검증\n",
    "from sklearn.model_selection import cross_val_score, cross_validate\n",
    "\n",
    "#각 폴드의 스코어\n",
    "scores = cross_val_score(best_dt2, new_X, new_y, cv = 5)\n",
    "scores\n",
    "\n",
    "pd.DataFrame(cross_validate(best_dt, new_X, new_y, cv = 5))\n",
    "print('교차검증 평균: ', scores.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fd82652",
   "metadata": {},
   "source": [
    "### 학습결과평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "238cfd65-2810-468f-9f75-c811edc1eab5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "       기상 지연       0.84      0.77      0.80      1488\n",
      "       기상 취소       0.47      0.52      0.49       137\n",
      "          출발       0.94      0.96      0.95      5993\n",
      "\n",
      "    accuracy                           0.91      7618\n",
      "   macro avg       0.75      0.75      0.75      7618\n",
      "weighted avg       0.91      0.91      0.91      7618\n",
      "\n",
      "Accuracy of Decision Tree:  0.9116566027828826\n"
     ]
    }
   ],
   "source": [
    "#학습결과평가\n",
    "from sklearn.metrics import classification_report\n",
    "predict_dt2 = best_dt.predict(X_test2)\n",
    "print(classification_report(y_test2, predict_dt2, zero_division=0))\n",
    "accuracy = accuracy_score(y_test2, predict_dt2)\n",
    "print(\"Accuracy of Decision Tree: \", accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3b107e3-3a1f-49d1-93d1-a238eb74b68a",
   "metadata": {},
   "source": [
    "# 4. 모델링 - Multinomial Logistic Regression (2만개 SMOTE Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ab23efae-937e-47b0-8e3d-64ed81cb8959",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score, roc_auc_score, roc_curve\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import statsmodels.api as sm\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "788508f7-7a82-4196-a507-cf14661d99da",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_X = smote_data2[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "new_y = smote_data2['현황']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b9a4b9",
   "metadata": {},
   "source": [
    "### Hyper Parameter Tuning - GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f2035534-43bb-44bc-8602-6ed607b073b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Hyperparameters: {'C': 0.001, 'penalty': 'l2'}\n",
      "GridSearchCV Results:\n",
      "         C penalty  mean_test_score\n",
      "0   0.001      l2         0.603429\n",
      "3   1.000      l2         0.600976\n",
      "4  10.000      l2         0.600976\n",
      "2   0.100      l2         0.600881\n",
      "1   0.010      l2         0.600595\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# 테스트하고자 하는 파라미터 값들을 사전 타입으로 정의\n",
    "mlr = LogisticRegression(random_state=42, multi_class='multinomial', solver='saga')\n",
    "parameters = {'C': [0.001, 0.01, 0.1, 1, 10], 'penalty': ['l2']}\n",
    "\n",
    "# 테스트와 훈련 데이터 분할\n",
    "X_train2, X_test2, y_train2, y_test2 = train_test_split(new_X, new_y, test_size=0.3, random_state=100)\n",
    "\n",
    "# 데이터 스케일 조정\n",
    "scaler = StandardScaler()\n",
    "X_train_scaled2 = scaler.fit_transform(X_train2)\n",
    "X_test_scaled2 = scaler.transform(X_test2)\n",
    "\n",
    "# GridSearchCV를 사용하여 최적의 하이퍼파라미터 찾기\n",
    "grid_mlr2 = GridSearchCV(mlr, param_grid=parameters, cv=5)\n",
    "grid_mlr2.fit(X_train_scaled2, y_train2)\n",
    "\n",
    "# 결과를 DataFrame으로 표시\n",
    "result = pd.DataFrame(grid_mlr2.cv_results_['params'])\n",
    "result['mean_test_score'] = grid_mlr2.cv_results_['mean_test_score']\n",
    "result.sort_values(by='mean_test_score', ascending=False, inplace=True)\n",
    "\n",
    "# 결과 출력\n",
    "print(\"Best Hyperparameters:\", grid_mlr2.best_params_)\n",
    "print(\"GridSearchCV Results:\\n\", result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e79b0546-565d-47af-be59-8919cf6cbb70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(C=0.001, max_iter=1000, multi_class=&#x27;multinomial&#x27;,\n",
       "                   random_state=42, solver=&#x27;saga&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(C=0.001, max_iter=1000, multi_class=&#x27;multinomial&#x27;,\n",
       "                   random_state=42, solver=&#x27;saga&#x27;)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(C=0.001, max_iter=1000, multi_class='multinomial',\n",
       "                   random_state=42, solver='saga')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 최적의 하이퍼파라미터로 모델 생성\n",
    "best_mlr2 = LogisticRegression(random_state=42, multi_class='multinomial', solver='saga', max_iter = 1000, C=0.001, penalty='l2')\n",
    "best_mlr2.fit(X_train_scaled2, y_train2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05a70a65",
   "metadata": {},
   "source": [
    "### 교차검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d23e0c3c-1072-448d-b8c4-a15473d3860f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n",
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차검증 평균:  0.5976833333333333\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fit_time</th>\n",
       "      <th>score_time</th>\n",
       "      <th>test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21.400406</td>\n",
       "      <td>0.015907</td>\n",
       "      <td>0.617417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23.474104</td>\n",
       "      <td>0.019804</td>\n",
       "      <td>0.579667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24.938997</td>\n",
       "      <td>0.015675</td>\n",
       "      <td>0.597250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28.040231</td>\n",
       "      <td>0.027064</td>\n",
       "      <td>0.598250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.918604</td>\n",
       "      <td>0.026551</td>\n",
       "      <td>0.595833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    fit_time  score_time  test_score\n",
       "0  21.400406    0.015907    0.617417\n",
       "1  23.474104    0.019804    0.579667\n",
       "2  24.938997    0.015675    0.597250\n",
       "3  28.040231    0.027064    0.598250\n",
       "4  20.918604    0.026551    0.595833"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 교차검증\n",
    "from sklearn.model_selection import cross_val_score, cross_validate\n",
    "\n",
    "# 교차 검증 수행\n",
    "scores = cross_val_score(best_mlr2, new_X, new_y, cv=5)\n",
    "cv_results = cross_validate(best_mlr2, new_X, new_y, cv=5)\n",
    "\n",
    "print('교차검증 평균: ', scores.mean())\n",
    "pd.DataFrame(cv_results)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90fcafa6",
   "metadata": {},
   "source": [
    "### 학습결과평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c8656072-722a-4ebf-9f1f-77a16a7e8f64",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "       기상 지연       0.64      0.65      0.65      5862\n",
      "       기상 취소       0.59      0.62      0.60      6134\n",
      "          출발       0.58      0.54      0.56      6004\n",
      "\n",
      "    accuracy                           0.60     18000\n",
      "   macro avg       0.60      0.60      0.60     18000\n",
      "weighted avg       0.60      0.60      0.60     18000\n",
      "\n",
      "Accuracy of Multinomial Logistic Regression:  0.6040555555555556\n"
     ]
    }
   ],
   "source": [
    "# 학습 결과 평가\n",
    "from sklearn.metrics import classification_report, accuracy_score\n",
    "predict_mlr2 = best_mlr2.predict(X_test_scaled2)\n",
    "print(classification_report(y_test2, predict_mlr2, zero_division=0))\n",
    "accuracy = accuracy_score(y_test2, predict_mlr2)\n",
    "print(\"Accuracy of Multinomial Logistic Regression: \", accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f4a0873",
   "metadata": {},
   "source": [
    "# 4. 모델링 - Random Forest (2만개 SMOTE Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b069c3e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import sklearn.metrics as mt\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f942548d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(42000, 6) (18000, 6) (42000,) (18000,)\n"
     ]
    }
   ],
   "source": [
    "new_X = smote_data2[[\"온도\", '시정', '전운량', '최저운고', '풍속', '강수량(mm)']]\n",
    "new_y = smote_data2['현황']\n",
    "#test, training (7:3 분할)\n",
    "X_train2, X_test2, y_train2, y_test2 = train_test_split(new_X,new_y,test_size = 0.3, random_state = 100)\n",
    "print(X_train2.shape, X_test2.shape, y_train2.shape, y_test2.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88bb07b2",
   "metadata": {},
   "source": [
    "### Hyper Parameter Tuning - GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7b0a73ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "\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>max_depth</th>\n",
       "      <th>min_samples_split</th>\n",
       "      <th>n_estimators</th>\n",
       "      <th>mean_test_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>0.878405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>130</td>\n",
       "      <td>0.878381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>0.878238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>150</td>\n",
       "      <td>0.878095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>150</td>\n",
       "      <td>0.878048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.878024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.878024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>130</td>\n",
       "      <td>0.877857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>150</td>\n",
       "      <td>0.876857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>0.876690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.876548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>130</td>\n",
       "      <td>0.876452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>150</td>\n",
       "      <td>0.873333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.873238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>150</td>\n",
       "      <td>0.873190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.873119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.872857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.872833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.872524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.872452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>150</td>\n",
       "      <td>0.872405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.872357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.872143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>20</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.872095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>150</td>\n",
       "      <td>0.779881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>140</td>\n",
       "      <td>0.779571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>120</td>\n",
       "      <td>0.779524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>130</td>\n",
       "      <td>0.779476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>140</td>\n",
       "      <td>0.779167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>150</td>\n",
       "      <td>0.779000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>120</td>\n",
       "      <td>0.778738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>130</td>\n",
       "      <td>0.778571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    max_depth  min_samples_split  n_estimators  mean_test_score\n",
       "16         30                  4           120         0.878405\n",
       "17         30                  4           130         0.878381\n",
       "24         40                  4           120         0.878238\n",
       "27         40                  4           150         0.878095\n",
       "19         30                  4           150         0.878048\n",
       "26         40                  4           140         0.878024\n",
       "18         30                  4           140         0.878024\n",
       "25         40                  4           130         0.877857\n",
       "11         20                  4           150         0.876857\n",
       "8          20                  4           120         0.876690\n",
       "10         20                  4           140         0.876548\n",
       "9          20                  4           130         0.876452\n",
       "23         30                  8           150         0.873333\n",
       "22         30                  8           140         0.873238\n",
       "31         40                  8           150         0.873190\n",
       "30         40                  8           140         0.873119\n",
       "21         30                  8           130         0.872857\n",
       "29         40                  8           130         0.872833\n",
       "28         40                  8           120         0.872524\n",
       "20         30                  8           120         0.872452\n",
       "15         20                  8           150         0.872405\n",
       "12         20                  8           120         0.872357\n",
       "14         20                  8           140         0.872143\n",
       "13         20                  8           130         0.872095\n",
       "3          10                  4           150         0.779881\n",
       "2          10                  4           140         0.779571\n",
       "0          10                  4           120         0.779524\n",
       "1          10                  4           130         0.779476\n",
       "6          10                  8           140         0.779167\n",
       "7          10                  8           150         0.779000\n",
       "4          10                  8           120         0.778738\n",
       "5          10                  8           130         0.778571"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#하이퍼 파라미터 튜닝(그리드 서치)5\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "#테스트하고자 하는 파라미터 값들을 사전 타입으로 정의\n",
    "rf7 = RandomForestClassifier(random_state=0)\n",
    "\n",
    "parameters = {'n_estimators': [120, 130, 140, 150],\n",
    "              'max_depth': [10, 20, 30, 40],\n",
    "              'min_samples_split': [4, 8]}\n",
    "\n",
    "grid_rf5 = GridSearchCV(rf7, # estimator 객체,\n",
    "                      param_grid = parameters, cv = 5\n",
    "                      # n_jobs = -1: 모든 cpu를 사용)\n",
    "                      )\n",
    "\n",
    "grid_rf5.fit(X_train2, y_train2)\n",
    "\n",
    "result = pd.DataFrame(grid_rf5.cv_results_['params'])\n",
    "result['mean_test_score'] = grid_rf5.cv_results_['mean_test_score']\n",
    "result.sort_values(by='mean_test_score', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "380a4380",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Parameters for Random Forest: {'max_depth': 30, 'min_samples_split': 4, 'n_estimators': 120}\n",
      "Accuracy of the Best Random Forest model: 0.8826111111111111\n"
     ]
    }
   ],
   "source": [
    "best_params_rf = grid_rf5.best_params_  \n",
    "print(\"Best Parameters for Random Forest:\", best_params_rf)\n",
    "\n",
    "#최적 파라미터 조합으로 RandomForestClassifier 초기화\n",
    "best_rf2 = RandomForestClassifier(**best_params_rf)\n",
    "\n",
    "#최적모델로 학습\n",
    "best_rf2.fit(X_train2, y_train2)\n",
    "\n",
    "# 최적 모델 평가\n",
    "predict3 = best_rf2.predict(X_test2)\n",
    "print(\"Accuracy of the Best Random Forest model:\", accuracy_score(y_test2,predict3)) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ecbe3b9",
   "metadata": {},
   "source": [
    "### 교차검증"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "defce724",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "교차검증 평균 - Accuracy: 0.8882, Precision: 0.8895, Recall: 0.8882, F1: 0.8882\n"
     ]
    }
   ],
   "source": [
    "# #교차검증: 검증데이터셋 나눠서 평가하기 (데이터셋: training, test, validation 으로 나눔)\n",
    "\n",
    "from sklearn.model_selection import cross_validate\n",
    "\n",
    "# 여러 평가 지표를 지정\n",
    "scoring = ['accuracy', 'precision_macro', 'recall_macro', 'f1_macro']\n",
    "\n",
    "# cross_validate를 사용하여 교차 검증 수행\n",
    "cv_results = cross_validate(best_rf2, new_X, new_y, cv=5, scoring=scoring)\n",
    "\n",
    "# 결과 출력\n",
    "result_df = pd.DataFrame({\n",
    "    'Accuracy': cv_results['test_accuracy'],\n",
    "    'Precision': cv_results['test_precision_macro'],\n",
    "    'Recall': cv_results['test_recall_macro'],\n",
    "    'F1': cv_results['test_f1_macro']\n",
    "})\n",
    "\n",
    "# 교차검증 평균 출력\n",
    "print('교차검증 평균 - Accuracy: {:.4f}, Precision: {:.4f}, Recall: {:.4f}, F1: {:.4f}'.format(\n",
    "    result_df['Accuracy'].mean(),\n",
    "    result_df['Precision'].mean(),\n",
    "    result_df['Recall'].mean(),\n",
    "    result_df['F1'].mean()\n",
    "))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "870c60bc",
   "metadata": {},
   "source": [
    "### 학습결과평가"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0caab30f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Data:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "       기상 지연       0.88      0.86      0.87      5862\n",
      "       기상 취소       0.92      0.92      0.92      6134\n",
      "          출발       0.84      0.87      0.86      6004\n",
      "\n",
      "    accuracy                           0.88     18000\n",
      "   macro avg       0.88      0.88      0.88     18000\n",
      "weighted avg       0.88      0.88      0.88     18000\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "\n",
    "print('Test Data:\\n', classification_report(y_test2, predict3, zero_division=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea44ec07",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b69dbc2e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86f370e3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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