Rain_Forecast.ipynb

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          "text": [
            "C:\\Users\\82105\\Anaconda3\\lib\\importlib\\_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
            "  return f(*args, **kwds)\n",
            "\n",
            "Bad key \"text.kerning_factor\" on line 4 in\n",
            "C:\\Users\\82105\\Anaconda3\\lib\\site-packages\\matplotlib\\mpl-data\\stylelib\\_classic_test_patch.mplstyle.\n",
            "You probably need to get an updated matplotlibrc file from\n",
            "https://github.com/matplotlib/matplotlib/blob/v3.1.3/matplotlibrc.template\n",
            "or from the matplotlib source distribution\n",
            "C:\\Users\\82105\\Anaconda3\\lib\\importlib\\_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
            "  return f(*args, **kwds)\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt   #그래프 출력시\n",
        "import matplotlib as mpl    #그래프 옵션\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "\n",
        "sns.set_style('darkgrid')\n",
        "\n",
        "#그래프 시각화 옵션 설정함수\n",
        "%matplotlib inline\n",
        "\n",
        "#그래프의 한글설정\n",
        "mpl.rc('font',family='Malgun Gothic')\n",
        "\n",
        "#그래프의 한글을 더욱 선명하게 출력\n",
        "from IPython.display import set_matplotlib_formats\n",
        "set_matplotlib_formats('retina')\n",
        "\n",
        "#그래프에서 음수 값이 나올 때, 깨지는 현상 방지\n",
        "mpl.rc('axes',unicode_minus=False)"
      ]
    },
    {
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      "metadata": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Location</th>\n",
              "      <th>MinTemp</th>\n",
              "      <th>MaxTemp</th>\n",
              "      <th>Rainfall</th>\n",
              "      <th>Evaporation</th>\n",
              "      <th>Sunshine</th>\n",
              "      <th>WindGustDir</th>\n",
              "      <th>WindGustSpeed</th>\n",
              "      <th>WindDir9am</th>\n",
              "      <th>...</th>\n",
              "      <th>Humidity3pm</th>\n",
              "      <th>Pressure9am</th>\n",
              "      <th>Pressure3pm</th>\n",
              "      <th>Cloud9am</th>\n",
              "      <th>Cloud3pm</th>\n",
              "      <th>Temp9am</th>\n",
              "      <th>Temp3pm</th>\n",
              "      <th>RainToday</th>\n",
              "      <th>RISK_MM</th>\n",
              "      <th>RainTomorrow</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008-12-01</td>\n",
              "      <td>Albury</td>\n",
              "      <td>13.4</td>\n",
              "      <td>22.9</td>\n",
              "      <td>0.6</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>W</td>\n",
              "      <td>44.0</td>\n",
              "      <td>W</td>\n",
              "      <td>...</td>\n",
              "      <td>22.0</td>\n",
              "      <td>1007.7</td>\n",
              "      <td>1007.1</td>\n",
              "      <td>8.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>16.9</td>\n",
              "      <td>21.8</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008-12-02</td>\n",
              "      <td>Albury</td>\n",
              "      <td>7.4</td>\n",
              "      <td>25.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WNW</td>\n",
              "      <td>44.0</td>\n",
              "      <td>NNW</td>\n",
              "      <td>...</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1010.6</td>\n",
              "      <td>1007.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17.2</td>\n",
              "      <td>24.3</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2008-12-03</td>\n",
              "      <td>Albury</td>\n",
              "      <td>12.9</td>\n",
              "      <td>25.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>WSW</td>\n",
              "      <td>46.0</td>\n",
              "      <td>W</td>\n",
              "      <td>...</td>\n",
              "      <td>30.0</td>\n",
              "      <td>1007.6</td>\n",
              "      <td>1008.7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>23.2</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2008-12-04</td>\n",
              "      <td>Albury</td>\n",
              "      <td>9.2</td>\n",
              "      <td>28.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NE</td>\n",
              "      <td>24.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>...</td>\n",
              "      <td>16.0</td>\n",
              "      <td>1017.6</td>\n",
              "      <td>1012.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>18.1</td>\n",
              "      <td>26.5</td>\n",
              "      <td>No</td>\n",
              "      <td>1.0</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2008-12-05</td>\n",
              "      <td>Albury</td>\n",
              "      <td>17.5</td>\n",
              "      <td>32.3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>W</td>\n",
              "      <td>41.0</td>\n",
              "      <td>ENE</td>\n",
              "      <td>...</td>\n",
              "      <td>33.0</td>\n",
              "      <td>1010.8</td>\n",
              "      <td>1006.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>29.7</td>\n",
              "      <td>No</td>\n",
              "      <td>0.2</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>142188</th>\n",
              "      <td>2017-06-20</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>3.5</td>\n",
              "      <td>21.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>31.0</td>\n",
              "      <td>ESE</td>\n",
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              "      <td>27.0</td>\n",
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              "      <td>1021.2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.4</td>\n",
              "      <td>20.9</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>No</td>\n",
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              "    <tr>\n",
              "      <th>142189</th>\n",
              "      <td>2017-06-21</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>2.8</td>\n",
              "      <td>23.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>E</td>\n",
              "      <td>31.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>...</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1024.6</td>\n",
              "      <td>1020.3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.1</td>\n",
              "      <td>22.4</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>142190</th>\n",
              "      <td>2017-06-22</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>3.6</td>\n",
              "      <td>25.3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NNW</td>\n",
              "      <td>22.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>...</td>\n",
              "      <td>21.0</td>\n",
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              "      <td>1019.1</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>No</td>\n",
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              "      <td>No</td>\n",
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              "    <tr>\n",
              "      <th>142191</th>\n",
              "      <td>2017-06-23</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>5.4</td>\n",
              "      <td>26.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>37.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>...</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1021.0</td>\n",
              "      <td>1016.8</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.5</td>\n",
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              "      <td>No</td>\n",
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              "      <td>No</td>\n",
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              "      <th>142192</th>\n",
              "      <td>2017-06-24</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>7.8</td>\n",
              "      <td>27.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>SE</td>\n",
              "      <td>28.0</td>\n",
              "      <td>SSE</td>\n",
              "      <td>...</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1019.4</td>\n",
              "      <td>1016.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>15.1</td>\n",
              "      <td>26.0</td>\n",
              "      <td>No</td>\n",
              "      <td>0.0</td>\n",
              "      <td>No</td>\n",
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              "<p>142193 rows × 24 columns</p>\n",
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            ],
            "text/plain": [
              "              Date Location  MinTemp  MaxTemp  Rainfall  Evaporation  \\\n",
              "0       2008-12-01   Albury     13.4     22.9       0.6          NaN   \n",
              "1       2008-12-02   Albury      7.4     25.1       0.0          NaN   \n",
              "2       2008-12-03   Albury     12.9     25.7       0.0          NaN   \n",
              "3       2008-12-04   Albury      9.2     28.0       0.0          NaN   \n",
              "4       2008-12-05   Albury     17.5     32.3       1.0          NaN   \n",
              "...            ...      ...      ...      ...       ...          ...   \n",
              "142188  2017-06-20    Uluru      3.5     21.8       0.0          NaN   \n",
              "142189  2017-06-21    Uluru      2.8     23.4       0.0          NaN   \n",
              "142190  2017-06-22    Uluru      3.6     25.3       0.0          NaN   \n",
              "142191  2017-06-23    Uluru      5.4     26.9       0.0          NaN   \n",
              "142192  2017-06-24    Uluru      7.8     27.0       0.0          NaN   \n",
              "\n",
              "        Sunshine WindGustDir  WindGustSpeed WindDir9am  ... Humidity3pm  \\\n",
              "0            NaN           W           44.0          W  ...        22.0   \n",
              "1            NaN         WNW           44.0        NNW  ...        25.0   \n",
              "2            NaN         WSW           46.0          W  ...        30.0   \n",
              "3            NaN          NE           24.0         SE  ...        16.0   \n",
              "4            NaN           W           41.0        ENE  ...        33.0   \n",
              "...          ...         ...            ...        ...  ...         ...   \n",
              "142188       NaN           E           31.0        ESE  ...        27.0   \n",
              "142189       NaN           E           31.0         SE  ...        24.0   \n",
              "142190       NaN         NNW           22.0         SE  ...        21.0   \n",
              "142191       NaN           N           37.0         SE  ...        24.0   \n",
              "142192       NaN          SE           28.0        SSE  ...        24.0   \n",
              "\n",
              "        Pressure9am  Pressure3pm  Cloud9am  Cloud3pm  Temp9am  Temp3pm  \\\n",
              "0            1007.7       1007.1       8.0       NaN     16.9     21.8   \n",
              "1            1010.6       1007.8       NaN       NaN     17.2     24.3   \n",
              "2            1007.6       1008.7       NaN       2.0     21.0     23.2   \n",
              "3            1017.6       1012.8       NaN       NaN     18.1     26.5   \n",
              "4            1010.8       1006.0       7.0       8.0     17.8     29.7   \n",
              "...             ...          ...       ...       ...      ...      ...   \n",
              "142188       1024.7       1021.2       NaN       NaN      9.4     20.9   \n",
              "142189       1024.6       1020.3       NaN       NaN     10.1     22.4   \n",
              "142190       1023.5       1019.1       NaN       NaN     10.9     24.5   \n",
              "142191       1021.0       1016.8       NaN       NaN     12.5     26.1   \n",
              "142192       1019.4       1016.5       3.0       2.0     15.1     26.0   \n",
              "\n",
              "        RainToday  RISK_MM  RainTomorrow  \n",
              "0              No      0.0            No  \n",
              "1              No      0.0            No  \n",
              "2              No      0.0            No  \n",
              "3              No      1.0            No  \n",
              "4              No      0.2            No  \n",
              "...           ...      ...           ...  \n",
              "142188         No      0.0            No  \n",
              "142189         No      0.0            No  \n",
              "142190         No      0.0            No  \n",
              "142191         No      0.0            No  \n",
              "142192         No      0.0            No  \n",
              "\n",
              "[142193 rows x 24 columns]"
            ]
          },
          "execution_count": 5,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "weather=pd.read_csv('weatherAUS.csv')\n",
        "weather"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AtvFqVgx8oYV"
      },
      "source": [
        "# PreProcessing"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "41T1sHxP8oYW"
      },
      "source": [
        "## 결측치 처리"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Hh3195lV8oYW",
        "outputId": "95a512f0-60c4-4760-c11a-ea099be9ed17"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Date                 0\n",
              "Location             0\n",
              "MinTemp            637\n",
              "MaxTemp            322\n",
              "Rainfall          1406\n",
              "Evaporation      60843\n",
              "Sunshine         67816\n",
              "WindGustDir       9330\n",
              "WindGustSpeed     9270\n",
              "WindDir9am       10013\n",
              "WindDir3pm        3778\n",
              "WindSpeed9am      1348\n",
              "WindSpeed3pm      2630\n",
              "Humidity9am       1774\n",
              "Humidity3pm       3610\n",
              "Pressure9am      14014\n",
              "Pressure3pm      13981\n",
              "Cloud9am         53657\n",
              "Cloud3pm         57094\n",
              "Temp9am            904\n",
              "Temp3pm           2726\n",
              "RainToday         1406\n",
              "RISK_MM              0\n",
              "RainTomorrow         0\n",
              "dtype: int64"
            ]
          },
          "execution_count": 4,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "weather.isna().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "usKTH4We8oYW"
      },
      "source": [
        "**Rainfall,Evaporation,Sunshine,Cloud9am,Cloud3pm는 drop**\n",
        "\n",
        "**RISK_MM도 변수 특성상 drop해주어야함**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bUWELKnL8oYX"
      },
      "outputs": [],
      "source": [
        "weather.drop(columns=['Evaporation','Sunshine','Pressure9am',\n",
        "                      'RISK_MM','Pressure3pm', 'Cloud9am', 'Cloud3pm'],axis=1,inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mXOS3yJK8oYX"
      },
      "outputs": [],
      "source": [
        "weather=weather.dropna()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cViWSyIo8oYX",
        "outputId": "e413582f-f906-4f25-d6b6-bb9b717bd379",
        "scrolled": false
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      "outputs": [
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              "        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>Date</th>\n",
              "      <th>Location</th>\n",
              "      <th>MinTemp</th>\n",
              "      <th>MaxTemp</th>\n",
              "      <th>Rainfall</th>\n",
              "      <th>WindGustDir</th>\n",
              "      <th>WindGustSpeed</th>\n",
              "      <th>WindDir9am</th>\n",
              "      <th>WindDir3pm</th>\n",
              "      <th>WindSpeed9am</th>\n",
              "      <th>WindSpeed3pm</th>\n",
              "      <th>Humidity9am</th>\n",
              "      <th>Humidity3pm</th>\n",
              "      <th>Temp9am</th>\n",
              "      <th>Temp3pm</th>\n",
              "      <th>RainToday</th>\n",
              "      <th>RainTomorrow</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008-12-01</td>\n",
              "      <td>Albury</td>\n",
              "      <td>13.4</td>\n",
              "      <td>22.9</td>\n",
              "      <td>0.6</td>\n",
              "      <td>W</td>\n",
              "      <td>44.0</td>\n",
              "      <td>W</td>\n",
              "      <td>WNW</td>\n",
              "      <td>20.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>16.9</td>\n",
              "      <td>21.8</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008-12-02</td>\n",
              "      <td>Albury</td>\n",
              "      <td>7.4</td>\n",
              "      <td>25.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>WNW</td>\n",
              "      <td>44.0</td>\n",
              "      <td>NNW</td>\n",
              "      <td>WSW</td>\n",
              "      <td>4.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.2</td>\n",
              "      <td>24.3</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2008-12-03</td>\n",
              "      <td>Albury</td>\n",
              "      <td>12.9</td>\n",
              "      <td>25.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>WSW</td>\n",
              "      <td>46.0</td>\n",
              "      <td>W</td>\n",
              "      <td>WSW</td>\n",
              "      <td>19.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>23.2</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2008-12-04</td>\n",
              "      <td>Albury</td>\n",
              "      <td>9.2</td>\n",
              "      <td>28.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NE</td>\n",
              "      <td>24.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>E</td>\n",
              "      <td>11.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>18.1</td>\n",
              "      <td>26.5</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2008-12-05</td>\n",
              "      <td>Albury</td>\n",
              "      <td>17.5</td>\n",
              "      <td>32.3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>W</td>\n",
              "      <td>41.0</td>\n",
              "      <td>ENE</td>\n",
              "      <td>NW</td>\n",
              "      <td>7.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>29.7</td>\n",
              "      <td>No</td>\n",
              "      <td>No</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121785</th>\n",
              "      <td>2017-06-20</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>3.5</td>\n",
              "      <td>21.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>E</td>\n",
              "      <td>31.0</td>\n",
              "      <td>ESE</td>\n",
              "      <td>E</td>\n",
              "      <td>15.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>9.4</td>\n",
              "      <td>20.9</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121786</th>\n",
              "      <td>2017-06-21</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>2.8</td>\n",
              "      <td>23.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>E</td>\n",
              "      <td>31.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>ENE</td>\n",
              "      <td>13.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>10.1</td>\n",
              "      <td>22.4</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121787</th>\n",
              "      <td>2017-06-22</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>3.6</td>\n",
              "      <td>25.3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NNW</td>\n",
              "      <td>22.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>N</td>\n",
              "      <td>13.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>10.9</td>\n",
              "      <td>24.5</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121788</th>\n",
              "      <td>2017-06-23</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>5.4</td>\n",
              "      <td>26.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>N</td>\n",
              "      <td>37.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>WNW</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>12.5</td>\n",
              "      <td>26.1</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121789</th>\n",
              "      <td>2017-06-24</td>\n",
              "      <td>Uluru</td>\n",
              "      <td>7.8</td>\n",
              "      <td>27.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>SE</td>\n",
              "      <td>28.0</td>\n",
              "      <td>SSE</td>\n",
              "      <td>N</td>\n",
              "      <td>13.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>51.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>15.1</td>\n",
              "      <td>26.0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>121790 rows × 17 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              Date Location  MinTemp  MaxTemp  Rainfall WindGustDir  \\\n",
              "0       2008-12-01   Albury     13.4     22.9       0.6           W   \n",
              "1       2008-12-02   Albury      7.4     25.1       0.0         WNW   \n",
              "2       2008-12-03   Albury     12.9     25.7       0.0         WSW   \n",
              "3       2008-12-04   Albury      9.2     28.0       0.0          NE   \n",
              "4       2008-12-05   Albury     17.5     32.3       1.0           W   \n",
              "...            ...      ...      ...      ...       ...         ...   \n",
              "121785  2017-06-20    Uluru      3.5     21.8       0.0           E   \n",
              "121786  2017-06-21    Uluru      2.8     23.4       0.0           E   \n",
              "121787  2017-06-22    Uluru      3.6     25.3       0.0         NNW   \n",
              "121788  2017-06-23    Uluru      5.4     26.9       0.0           N   \n",
              "121789  2017-06-24    Uluru      7.8     27.0       0.0          SE   \n",
              "\n",
              "        WindGustSpeed WindDir9am WindDir3pm  WindSpeed9am  WindSpeed3pm  \\\n",
              "0                44.0          W        WNW          20.0          24.0   \n",
              "1                44.0        NNW        WSW           4.0          22.0   \n",
              "2                46.0          W        WSW          19.0          26.0   \n",
              "3                24.0         SE          E          11.0           9.0   \n",
              "4                41.0        ENE         NW           7.0          20.0   \n",
              "...               ...        ...        ...           ...           ...   \n",
              "121785           31.0        ESE          E          15.0          13.0   \n",
              "121786           31.0         SE        ENE          13.0          11.0   \n",
              "121787           22.0         SE          N          13.0           9.0   \n",
              "121788           37.0         SE        WNW           9.0           9.0   \n",
              "121789           28.0        SSE          N          13.0           7.0   \n",
              "\n",
              "        Humidity9am  Humidity3pm  Temp9am  Temp3pm RainToday RainTomorrow  \n",
              "0              71.0         22.0     16.9     21.8        No           No  \n",
              "1              44.0         25.0     17.2     24.3        No           No  \n",
              "2              38.0         30.0     21.0     23.2        No           No  \n",
              "3              45.0         16.0     18.1     26.5        No           No  \n",
              "4              82.0         33.0     17.8     29.7        No           No  \n",
              "...             ...          ...      ...      ...       ...          ...  \n",
              "121785         59.0         27.0      9.4     20.9        No           No  \n",
              "121786         51.0         24.0     10.1     22.4        No           No  \n",
              "121787         56.0         21.0     10.9     24.5        No           No  \n",
              "121788         53.0         24.0     12.5     26.1        No           No  \n",
              "121789         51.0         24.0     15.1     26.0        No           No  \n",
              "\n",
              "[121790 rows x 17 columns]"
            ]
          },
          "execution_count": 8,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "weather.reset_index(drop=True,inplace=True)\n",
        "weather"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E2WYShFK8oYY"
      },
      "source": [
        "## 파생변수 생성"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FNfmFWua8oYY"
      },
      "outputs": [],
      "source": [
        "def season(data):\n",
        "    data=str(data)\n",
        "    data=data.split('-')[1]\n",
        "    return data\n",
        "\n",
        "weather['month']=weather['Date'].apply(season)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nZgvm9ra8oYY"
      },
      "source": [
        "#호주의 계절 분기에 따라 봄-1, 여름-2, 가을-3, 겨울-4로 매핑"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "30MNL72Y8oYY"
      },
      "outputs": [],
      "source": [
        "weather['season']=weather['month'].replace(['12','01','02'],2).replace(['03','04','05'],3).replace(['06','07','08'],4).replace(['09','10','11'],1)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fd2016Eo8oYZ"
      },
      "source": [
        "#호주에는 우기와 건기가 존재함 우기-1, 건기-0으로 매핑"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oRIpL7Xa8oYZ"
      },
      "outputs": [],
      "source": [
        "weather['rain_season']=weather['month'].replace(['11','12','01','02','03','04'],1).replace(['05','06','07','08','09','10'],0)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2NyKOSni8oYZ"
      },
      "source": [
        "# EDA"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vt4CL9f48oYZ",
        "outputId": "dea7d070-576d-41c7-ef81-f3573c937bc3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[Text(0.5, 0, 'MinTemp'),\n",
              " Text(1.5, 0, 'MaxTemp'),\n",
              " Text(2.5, 0, 'Rainfall'),\n",
              " Text(3.5, 0, 'WindGustSpeed'),\n",
              " Text(4.5, 0, 'WindSpeed9am'),\n",
              " Text(5.5, 0, 'WindSpeed3pm'),\n",
              " Text(6.5, 0, 'Humidity9am'),\n",
              " Text(7.5, 0, 'Humidity3pm'),\n",
              " Text(8.5, 0, 'Temp9am'),\n",
              " Text(9.5, 0, 'Temp3pm'),\n",
              " Text(10.5, 0, 'season'),\n",
              " Text(11.5, 0, 'rain_season')]"
            ]
          },
          "execution_count": 44,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 720x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 410,
              "width": 494
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "corr = weather.corr()\n",
        "plt.figure(figsize=(10,6))\n",
        "ax = sns.heatmap(\n",
        "    corr, \n",
        "    vmin=-1, vmax=1, center=0,\n",
        "    cmap=sns.diverging_palette(20, 220, n=200),\n",
        "    square=True\n",
        ")\n",
        "ax.set_xticklabels(\n",
        "    ax.get_xticklabels(),\n",
        "    rotation=45,\n",
        "    horizontalalignment='right'\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OdFz8HYz8oYa",
        "outputId": "1b75fe26-1d4b-40bd-99fc-8d8b33e6df97"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 373,
              "width": 498
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "sns.boxplot(x='RainTomorrow', y='WindGustSpeed', data=weather, palette='Set3')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8rK64jdI8oYa",
        "outputId": "98251038-ab89-40bb-8b2e-b97ef271dc31"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 466,
              "width": 888
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(15,8))\n",
        "a=weather['RainTomorrow'].unique()\n",
        "for i, name in enumerate(a):\n",
        "    sns.kdeplot(weather[weather['RainTomorrow'] == name]['Humidity3pm'], label=name,legend=True,shade=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EUoeMu-M8oYa",
        "outputId": "07879f29-063d-4c51-838e-b1c55d99806b"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 466,
              "width": 877
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure(figsize=(15,8))\n",
        "a=weather['season'].unique()\n",
        "for i, name in enumerate(a):\n",
        "    sns.kdeplot(weather[weather['season'] == name]['Temp3pm'], label=name,legend=True,shade=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XUrXvxm_8oYb"
      },
      "source": [
        "# Modeling"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "S1jbMYPG8oYb"
      },
      "outputs": [],
      "source": [
        "from lightgbm import LGBMClassifier\n",
        "from xgboost import XGBClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.metrics import accuracy_score,f1_score, confusion_matrix\n",
        "from sklearn.model_selection import KFold,cross_val_score\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.model_selection import GridSearchCV"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sx5o0VKt8oYb"
      },
      "source": [
        "## Label Encoding"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "J_gUL8U38oYb"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import LabelEncoder"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QJ6SsKad8oYb"
      },
      "outputs": [],
      "source": [
        "label_list=['Location','WindGustDir','WindDir9am','WindDir3pm']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QHYvLts78oYc"
      },
      "outputs": [],
      "source": [
        "for i in label_list:\n",
        "    y1=weather[[i]].values.tolist()\n",
        "    encoder=LabelEncoder()\n",
        "    encoder.fit(y1)\n",
        "    label1=encoder.transform(y1)\n",
        "    weather[i]=label1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Hlq9x9Tf8oYc"
      },
      "outputs": [],
      "source": [
        "weather['RainToday']=weather['RainToday'].replace('No',0).replace('Yes',1)\n",
        "weather['RainTomorrow']=weather['RainTomorrow'].replace('No',0).replace('Yes',1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7qiMsNCi8oYc",
        "outputId": "dce0a1f2-51aa-4944-96ea-0b12aab26462"
      },
      "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>Date</th>\n",
              "      <th>Location</th>\n",
              "      <th>MinTemp</th>\n",
              "      <th>MaxTemp</th>\n",
              "      <th>Rainfall</th>\n",
              "      <th>WindGustDir</th>\n",
              "      <th>WindGustSpeed</th>\n",
              "      <th>WindDir9am</th>\n",
              "      <th>WindDir3pm</th>\n",
              "      <th>WindSpeed9am</th>\n",
              "      <th>WindSpeed3pm</th>\n",
              "      <th>Humidity9am</th>\n",
              "      <th>Humidity3pm</th>\n",
              "      <th>Temp9am</th>\n",
              "      <th>Temp3pm</th>\n",
              "      <th>RainToday</th>\n",
              "      <th>RainTomorrow</th>\n",
              "      <th>month</th>\n",
              "      <th>season</th>\n",
              "      <th>rain_season</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008-12-01</td>\n",
              "      <td>1</td>\n",
              "      <td>13.4</td>\n",
              "      <td>22.9</td>\n",
              "      <td>0.6</td>\n",
              "      <td>13</td>\n",
              "      <td>44.0</td>\n",
              "      <td>13</td>\n",
              "      <td>14</td>\n",
              "      <td>20.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>16.9</td>\n",
              "      <td>21.8</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008-12-02</td>\n",
              "      <td>1</td>\n",
              "      <td>7.4</td>\n",
              "      <td>25.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14</td>\n",
              "      <td>44.0</td>\n",
              "      <td>6</td>\n",
              "      <td>15</td>\n",
              "      <td>4.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>17.2</td>\n",
              "      <td>24.3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2008-12-03</td>\n",
              "      <td>1</td>\n",
              "      <td>12.9</td>\n",
              "      <td>25.7</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15</td>\n",
              "      <td>46.0</td>\n",
              "      <td>13</td>\n",
              "      <td>15</td>\n",
              "      <td>19.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>23.2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2008-12-04</td>\n",
              "      <td>1</td>\n",
              "      <td>9.2</td>\n",
              "      <td>28.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>4</td>\n",
              "      <td>24.0</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>18.1</td>\n",
              "      <td>26.5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2008-12-05</td>\n",
              "      <td>1</td>\n",
              "      <td>17.5</td>\n",
              "      <td>32.3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>13</td>\n",
              "      <td>41.0</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>7.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>29.7</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Date  Location  MinTemp  MaxTemp  Rainfall  WindGustDir  \\\n",
              "0  2008-12-01         1     13.4     22.9       0.6           13   \n",
              "1  2008-12-02         1      7.4     25.1       0.0           14   \n",
              "2  2008-12-03         1     12.9     25.7       0.0           15   \n",
              "3  2008-12-04         1      9.2     28.0       0.0            4   \n",
              "4  2008-12-05         1     17.5     32.3       1.0           13   \n",
              "\n",
              "   WindGustSpeed  WindDir9am  WindDir3pm  WindSpeed9am  WindSpeed3pm  \\\n",
              "0           44.0          13          14          20.0          24.0   \n",
              "1           44.0           6          15           4.0          22.0   \n",
              "2           46.0          13          15          19.0          26.0   \n",
              "3           24.0           9           0          11.0           9.0   \n",
              "4           41.0           1           7           7.0          20.0   \n",
              "\n",
              "   Humidity9am  Humidity3pm  Temp9am  Temp3pm  RainToday  RainTomorrow month  \\\n",
              "0         71.0         22.0     16.9     21.8          0             0    12   \n",
              "1         44.0         25.0     17.2     24.3          0             0    12   \n",
              "2         38.0         30.0     21.0     23.2          0             0    12   \n",
              "3         45.0         16.0     18.1     26.5          0             0    12   \n",
              "4         82.0         33.0     17.8     29.7          0             0    12   \n",
              "\n",
              "   season  rain_season  \n",
              "0       2            1  \n",
              "1       2            1  \n",
              "2       2            1  \n",
              "3       2            1  \n",
              "4       2            1  "
            ]
          },
          "execution_count": 52,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "weather.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ITiPf-qE8oYc",
        "outputId": "b1a17b69-6bc3-4b7d-c3f6-d3c4d40d2767"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(121790, 20)"
            ]
          },
          "execution_count": 53,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "weather.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k-8dM8M_8oYd"
      },
      "source": [
        "## Train-Validation-Test Split"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jMNQPAej8oYd"
      },
      "outputs": [],
      "source": [
        "weather=weather[['Date','season','rain_season','Location', 'MinTemp', 'MaxTemp', 'Rainfall', 'WindGustDir',\n",
        "       'WindGustSpeed', 'WindDir9am', 'WindDir3pm', 'WindSpeed9am',\n",
        "       'WindSpeed3pm', 'Humidity9am', 'Humidity3pm', 'Temp9am', 'Temp3pm',\n",
        "       'RainToday', 'RainTomorrow']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-Rz3sWTO8oYd"
      },
      "outputs": [],
      "source": [
        "X=weather.iloc[:,1:18]\n",
        "Y=weather.iloc[:,18]\n",
        "\n",
        "X_train,X_test,Y_train,Y_test=train_test_split(X,Y,test_size=0.3,random_state=123)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kG0jyuFi8oYd",
        "outputId": "c6836946-f12b-412a-8af6-847c75e7b1a3",
        "scrolled": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "학습셋: (85253, 17) , (85253,)\n",
            "테스트셋: (36537, 17) , (36537,)\n"
          ]
        }
      ],
      "source": [
        "print('학습셋:',X_train.shape,',',Y_train.shape)\n",
        "print('테스트셋:',X_test.shape,',',Y_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "k_bD7cRl8oYe",
        "outputId": "a16a1d40-7221-423b-e60b-d740efbcf199"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x1d3b70dfc08>"
            ]
          },
          "execution_count": 138,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 263,
              "width": 398
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "sns.countplot(Y_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wWtjTeA48oYe",
        "outputId": "befac6c2-d7d1-4ac3-8bf0-dc8a412b79ac"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x1d3b70581c8>"
            ]
          },
          "execution_count": 139,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 267,
              "width": 398
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "sns.countplot(Y_test)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GHOHQNYS8oYe"
      },
      "source": [
        "## LigthGBM"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XxAnI1aT8oYe"
      },
      "source": [
        "### Feature Selection"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "JBYCw6-i8oYe",
        "outputId": "0829a9d5-ad84-4bc9-cbbe-423c3cd05a90"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.6223365172667158"
            ]
          },
          "execution_count": 27,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "lgb=LGBMClassifier()\n",
        "lgb.fit(X_train,Y_train)\n",
        "pred=lgb.predict(X_test)\n",
        "f1_score(Y_test,pred)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xsvrVqkV8oYf",
        "outputId": "d814f5c6-c21f-4a2f-e81d-6367494bfe8b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Modeling  1 st\n",
            "train set f1_score:  0.6505671026211538\n",
            "test set f1_score:  0.6039047326995809\n",
            "-----------------------------------------\n",
            "Modeling  2 st\n",
            "train set f1_score:  0.6546517291768144\n",
            "test set f1_score:  0.5982524632831381\n",
            "-----------------------------------------\n",
            "Modeling  3 st\n",
            "train set f1_score:  0.6502771618625277\n",
            "test set f1_score:  0.6070075757575758\n",
            "-----------------------------------------\n",
            "Modeling  4 st\n",
            "train set f1_score:  0.6377920255358961\n",
            "test set f1_score:  0.6211881635419021\n",
            "-----------------------------------------\n",
            "Modeling  5 st\n",
            "train set f1_score:  0.6456380870775986\n",
            "test set f1_score:  0.5982803916885597\n",
            "-----------------------------------------\n",
            "Mean test set f1_score:  0.6057266653941513\n"
          ]
        }
      ],
      "source": [
        "kfold=KFold(n_splits=5)\n",
        "cv_score=[]\n",
        "\n",
        "x=X.values\n",
        "y=Y.values\n",
        "model=LGBMClassifier()\n",
        "\n",
        "n_iter=0\n",
        "for train_index, test_index in kfold.split(x):\n",
        "    x_train, x_test=x[train_index],x[test_index]\n",
        "    y_train, y_test=y[train_index],y[test_index]\n",
        "    \n",
        "    model.fit(x_train,y_train)\n",
        "    y_pred_train=model.predict(x_train)\n",
        "    y_pred_test=model.predict(x_test)\n",
        "    \n",
        "    n_iter=n_iter+1\n",
        "    \n",
        "    acc_train=f1_score(y_train,y_pred_train)\n",
        "    acc_test=f1_score(y_test,y_pred_test)\n",
        "    cv_score.append(acc_test)\n",
        "    \n",
        "    print(\"Modeling \",n_iter,\"st\")\n",
        "    print('train set f1_score: ',acc_train)\n",
        "    print('test set f1_score: ',acc_test)\n",
        "    print(\"-----------------------------------------\")\n",
        "    \n",
        "print('Mean test set f1_score: ',np.mean(cv_score))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4RL6YQ3L8oYf",
        "outputId": "ba8ebcd2-f83b-4cda-8923-d77e69bb3c80"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x1d3bc0fc448>"
            ]
          },
          "execution_count": 49,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 720x864 with 1 Axes>"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 714,
              "width": 666
            },
            "needs_background": "light",
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "#변수중요도 plot\n",
        "from lightgbm import plot_importance\n",
        "lgb=LGBMClassifier()\n",
        "lgb.fit(X_train,Y_train)\n",
        "fig,ax=plt.subplots(figsize=(10,12))\n",
        "plot_importance(lgb,ax=ax)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kx-GpN5n8oYf"
      },
      "source": [
        "**=> rain_season까지 제거, 정해진 기준은 없으나 rain_season까지 제거했을때 더 좋은 성능임을 확인**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jFyZ4D7P8oYg"
      },
      "outputs": [],
      "source": [
        "feature=['Location','Humidity3pm','WindGustSpeed','MinTemp','Humidity9am','Temp3pm','Temp9am','WindDir3pm',\n",
        "        'WindGustDir','WindSpeed3pm','MaxTemp','Rainfall','WindDir9am','season']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RMFAzgER8oYg"
      },
      "outputs": [],
      "source": [
        "#선택된 변수들로만 다시 X,Y 구성\n",
        "X_=weather[feature]\n",
        "Y_=weather.iloc[:,18]\n",
        "\n",
        "X_train,X_test,Y_train,Y_test=train_test_split(X_,Y_,test_size=0.3,random_state=123)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rkMPUqTb8oYg",
        "outputId": "4eba49c1-bac4-4ab1-9405-5bcd9a8b3075"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "학습셋: (85253, 14) , (85253,)\n",
            "테스트셋: (36537, 14) , (36537,)\n"
          ]
        }
      ],
      "source": [
        "print('학습셋:',X_train.shape,',',Y_train.shape)\n",
        "print('테스트셋:',X_test.shape,',',Y_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QG_JqxjH8oYg",
        "outputId": "b9097041-6679-465d-9ba3-603e6c9e1496"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Modeling  1 st\n",
            "train set f1_score:  0.6499362435226133\n",
            "test set f1_score:  0.6052848885218828\n",
            "-----------------------------------------\n",
            "Modeling  2 st\n",
            "train set f1_score:  0.6525607638888888\n",
            "test set f1_score:  0.5991016282987086\n",
            "-----------------------------------------\n",
            "Modeling  3 st\n",
            "train set f1_score:  0.6493304870948962\n",
            "test set f1_score:  0.6072470588235294\n",
            "-----------------------------------------\n",
            "Modeling  4 st\n",
            "train set f1_score:  0.6376119075081013\n",
            "test set f1_score:  0.6229138475417231\n",
            "-----------------------------------------\n",
            "Modeling  5 st\n",
            "train set f1_score:  0.6444134378018676\n",
            "test set f1_score:  0.5997610513739545\n",
            "-----------------------------------------\n",
            "Mean test set f1_score:  0.6068616949119596\n"
          ]
        }
      ],
      "source": [
        "kfold=KFold(n_splits=5)\n",
        "cv_score=[]\n",
        "\n",
        "x=X_.values\n",
        "y=Y_.values\n",
        "model=LGBMClassifier()\n",
        "\n",
        "n_iter=0\n",
        "for train_index, test_index in kfold.split(x):\n",
        "    x_train, x_test=x[train_index],x[test_index]\n",
        "    y_train, y_test=y[train_index],y[test_index]\n",
        "    \n",
        "    model.fit(x_train,y_train)\n",
        "    y_pred_train=model.predict(x_train)\n",
        "    y_pred_test=model.predict(x_test)\n",
        "    \n",
        "    n_iter=n_iter+1\n",
        "    \n",
        "    acc_train=f1_score(y_train,y_pred_train)\n",
        "    acc_test=f1_score(y_test,y_pred_test)\n",
        "    cv_score.append(acc_test)\n",
        "    \n",
        "    print(\"Modeling \",n_iter,\"st\")\n",
        "    print('train set f1_score: ',acc_train)\n",
        "    print('test set f1_score: ',acc_test)\n",
        "    print(\"-----------------------------------------\")\n",
        "    \n",
        "print('Mean test set f1_score: ',np.mean(cv_score))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yhlGz0Ei8oYh"
      },
      "source": [
        "### Hyperparameter Tuning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wroXajGm8oYh"
      },
      "outputs": [],
      "source": [
        "model=LGBMClassifier()\n",
        "param={'max_depth':[-1,3,5],'num_leaves':[31,9,24],'n_estimators':[300,500,700],'learning_rate':[0.1,0.3],\n",
        "      'class_weight':[None,'balanced']}\n",
        "\n",
        "grid_model=GridSearchCV(model,param_grid=param, cv=5,scoring='f1')\n",
        "grid_model.fit(X_train,Y_train)\n",
        "result=pd.DataFrame(grid_model.cv_results_)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Dn33LOtL8oYh",
        "outputId": "e1b8c516-01be-49a7-a0d9-94011092d42f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'class_weight': 'balanced',\n",
              " 'learning_rate': 0.1,\n",
              " 'max_depth': -1,\n",
              " 'n_estimators': 700,\n",
              " 'num_leaves': 31}"
            ]
          },
          "execution_count": 27,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "grid_model.best_params_"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l0Vi-kDM8oYh"
      },
      "source": [
        "## XGBOOST"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RhyHKxyY8oYh",
        "outputId": "6378bec4-b9d0-428c-cc91-e93cdeb82d98"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Modeling  1 st\n",
            "train set f1_score:  0.5990409026798308\n",
            "test set f1_score:  0.58940325887558\n",
            "-----------------------------------------\n",
            "Modeling  2 st\n",
            "train set f1_score:  0.6052690835397432\n",
            "test set f1_score:  0.5907123179850453\n",
            "-----------------------------------------\n",
            "Modeling  3 st\n",
            "train set f1_score:  0.6000173065274453\n",
            "test set f1_score:  0.5826497128794094\n",
            "-----------------------------------------\n",
            "Modeling  4 st\n",
            "train set f1_score:  0.585518209690822\n",
            "test set f1_score:  0.5642274442956289\n",
            "-----------------------------------------\n",
            "Modeling  5 st\n",
            "train set f1_score:  0.5946579586368583\n",
            "test set f1_score:  0.5657794676806084\n",
            "-----------------------------------------\n",
            "Mean test set f1_score:  0.5785544403432544\n"
          ]
        }
      ],
      "source": [
        "kfold=KFold(n_splits=5)\n",
        "cv_score=[]\n",
        "\n",
        "x=X_.values\n",
        "y=Y_.values\n",
        "model=XGBClassifier()\n",
        "\n",
        "n_iter=0\n",
        "for train_index, test_index in kfold.split(x):\n",
        "    x_train, x_test=x[train_index],x[test_index]\n",
        "    y_train, y_test=y[train_index],y[test_index]\n",
        "    \n",
        "    model.fit(x_train,y_train)\n",
        "    y_pred_train=model.predict(x_train)\n",
        "    y_pred_test=model.predict(x_test)\n",
        "    \n",
        "    n_iter=n_iter+1\n",
        "    \n",
        "    acc_train=f1_score(y_train,y_pred_train)\n",
        "    acc_test=f1_score(y_test,y_pred_test)\n",
        "    cv_score.append(acc_test)\n",
        "    \n",
        "    print(\"Modeling \",n_iter,\"st\")\n",
        "    print('train set f1_score: ',acc_train)\n",
        "    print('test set f1_score: ',acc_test)\n",
        "    print(\"-----------------------------------------\")\n",
        "    \n",
        "print('Mean test set f1_score: ',np.mean(cv_score))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v6gdBfHj8oYi"
      },
      "source": [
        "### Hyperparameter Tuning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "uA3WcwIL8oYi"
      },
      "outputs": [],
      "source": [
        "model=XGBClassifier()\n",
        "param={'max_depth':[3,5,8],'scale_pos_weight':[1,3,5],'n_estimators':[200,300],'min_child_weight':[1,2,3]}\n",
        "\n",
        "grid_model=GridSearchCV(model,param_grid=param, cv=5,scoring='f1')\n",
        "grid_model.fit(X_train,Y_train)\n",
        "result1=pd.DataFrame(grid_model.cv_results_)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GoG2kDXj8oYi",
        "outputId": "78ce8826-8b7a-4d0f-e2cd-b08a7a8bf093"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'max_depth': 8,\n",
              " 'min_child_weight': 3,\n",
              " 'n_estimators': 300,\n",
              " 'scale_pos_weight': 3}"
            ]
          },
          "execution_count": 63,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "grid_model.best_params_"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lYLUu1cC8oYi"
      },
      "source": [
        "## RandomForest"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kVZW9tcg8oYi",
        "outputId": "6d58b23a-1fc0-4b6d-d614-c45423f14905",
        "scrolled": false
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Modeling  1 st\n",
            "train set f1_score:  0.9999068207230712\n",
            "test set f1_score:  0.5976465507934795\n",
            "-----------------------------------------\n",
            "Modeling  2 st\n",
            "train set f1_score:  0.9999533603843104\n",
            "test set f1_score:  0.59106529209622\n",
            "-----------------------------------------\n",
            "Modeling  3 st\n",
            "train set f1_score:  0.9999763151038582\n",
            "test set f1_score:  0.5886617661866881\n",
            "-----------------------------------------\n",
            "Modeling  4 st\n",
            "train set f1_score:  0.9999768673806935\n",
            "test set f1_score:  0.5986773407587886\n",
            "-----------------------------------------\n",
            "Modeling  5 st\n",
            "train set f1_score:  0.9999543399844756\n",
            "test set f1_score:  0.574928133983252\n",
            "-----------------------------------------\n",
            "Mean test set f1_score:  0.5901958167636856\n"
          ]
        }
      ],
      "source": [
        "kfold=KFold(n_splits=5)\n",
        "cv_score=[]\n",
        "\n",
        "x=X_.values\n",
        "y=Y_.values\n",
        "model=RandomForestClassifier()\n",
        "\n",
        "n_iter=0\n",
        "for train_index, test_index in kfold.split(x):\n",
        "    x_train, x_test=x[train_index],x[test_index]\n",
        "    y_train, y_test=y[train_index],y[test_index]\n",
        "    \n",
        "    model.fit(x_train,y_train)\n",
        "    y_pred_train=model.predict(x_train)\n",
        "    y_pred_test=model.predict(x_test)\n",
        "    \n",
        "    n_iter=n_iter+1\n",
        "    \n",
        "    acc_train=f1_score(y_train,y_pred_train)\n",
        "    acc_test=f1_score(y_test,y_pred_test)\n",
        "    cv_score.append(acc_test)\n",
        "    \n",
        "    print(\"Modeling \",n_iter,\"st\")\n",
        "    print('train set f1_score: ',acc_train)\n",
        "    print('test set f1_score: ',acc_test)\n",
        "    print(\"-----------------------------------------\")\n",
        "    \n",
        "print('Mean test set f1_score: ',np.mean(cv_score))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M3z_NnXG8oYj"
      },
      "source": [
        "### Hyperparameter Tuning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wbHADPkb8oYj",
        "outputId": "bef046d2-541b-4ad5-f447-b3ed709a3588"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n",
              "                       criterion='gini', max_depth=None, max_features='auto',\n",
              "                       max_leaf_nodes=None, max_samples=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, n_estimators=100,\n",
              "                       n_jobs=None, oob_score=False, random_state=None,\n",
              "                       verbose=0, warm_start=False)"
            ]
          },
          "execution_count": 19,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "RandomForestClassifier()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qerl-IWu8oYj"
      },
      "outputs": [],
      "source": [
        "model=RandomForestClassifier()\n",
        "param={'max_depth':[None,5,8],'class_weight':[None,'balanced'],'n_estimators':[100,200,300],'min_samples_split':[2,3,4]}\n",
        "\n",
        "grid_model=GridSearchCV(model,param_grid=param, cv=5,scoring='f1')\n",
        "grid_model.fit(X_train,Y_train)\n",
        "result2=pd.DataFrame(grid_model.cv_results_)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "o0jdSlCD8oYj",
        "outputId": "64280b28-3bd5-44ab-b6b7-be2109b68f31"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'class_weight': 'balanced',\n",
              " 'max_depth': 8,\n",
              " 'min_samples_split': 2,\n",
              " 'n_estimators': 100}"
            ]
          },
          "execution_count": 65,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "grid_model.best_params_"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6Bdm0sCr8oYj"
      },
      "source": [
        "# Final Stacking"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SqcFOQEE8oYk"
      },
      "outputs": [],
      "source": [
        "lgb=LGBMClassifier(class_weight='balanced',n_estimators=700)\n",
        "xgb=XGBClassifier(scale_pos_weight=3,max_depth=8,min_child_weight=3,n_estimators=300)\n",
        "rf=RandomForestClassifier(class_weight='balanced',max_depth=8,min_samples_split=2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "m47nZj3j8oYk"
      },
      "outputs": [],
      "source": [
        "xgb_final=XGBClassifier(scale_pos_weight=3,max_depth=8,min_child_weight=3,n_estimators=300)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TzxMPelQ8oYk"
      },
      "outputs": [],
      "source": [
        "def get_stacking_base_datasets(model, X_train_n, y_train_n, X_test_n, n_folds ):\n",
        "    kf = KFold(n_splits=n_folds, shuffle=False, random_state=0)\n",
        "    train_fold_pred = np.zeros((X_train_n.shape[0] ,1 ))\n",
        "    test_pred = np.zeros((X_test_n.shape[0],n_folds))\n",
        "    print(model.__class__.__name__ , ' model start ')\n",
        "    \n",
        "    for folder_counter , (train_index, valid_index) in enumerate(kf.split(X_train_n)): \n",
        "        print('\\t fold set: ',folder_counter,' start ')\n",
        "        X_tr = X_train_n[train_index] \n",
        "        y_tr = y_train_n[train_index] \n",
        "        X_te = X_train_n[valid_index]  \n",
        "        \n",
        "    \n",
        "        model.fit(X_tr , y_tr)      \n",
        "        train_fold_pred[valid_index, :] = model.predict(X_te).reshape(-1,1) \n",
        "        test_pred[:, folder_counter] = model.predict(X_test_n)\n",
        "             \n",
        "    test_pred_mean = np.mean(test_pred, axis=1).reshape(-1,1)    \n",
        "    \n",
        "    return train_fold_pred , test_pred_mean"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ipzJh3yV8oYk",
        "outputId": "51131ba7-91d1-43b9-8cc1-78f231b1c2cd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "LGBMClassifier  model start \n",
            "\t fold set:  0  start \n",
            "\t fold set:  1  start \n",
            "\t fold set:  2  start \n",
            "\t fold set:  3  start \n",
            "\t fold set:  4  start \n",
            "XGBClassifier  model start \n",
            "\t fold set:  0  start \n",
            "\t fold set:  1  start \n",
            "\t fold set:  2  start \n",
            "\t fold set:  3  start \n",
            "\t fold set:  4  start \n",
            "RandomForestClassifier  model start \n",
            "\t fold set:  0  start \n",
            "\t fold set:  1  start \n",
            "\t fold set:  2  start \n",
            "\t fold set:  3  start \n",
            "\t fold set:  4  start \n"
          ]
        }
      ],
      "source": [
        "lgb_train, lgb_test = get_stacking_base_datasets(lgb, X_train.values, Y_train.values, X_test.values, 5)\n",
        "xgb_train, xgb_test = get_stacking_base_datasets(xgb, X_train.values, Y_train.values, X_test.values, 5)\n",
        "rf_train, rf_test = get_stacking_base_datasets(rf, X_train.values, Y_train.values, X_test.values,  5)    "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ezbtg1ek8oYl",
        "outputId": "01c5bd2b-ca13-44ae-f376-477ac4b28fc3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Original train feature Shape: (85253, 14) Original test feature Shape: (36537, 14)\n",
            "Stacking train feature Shape: (85253, 3) Stacking test feature 데이터 Shape: (36537, 3)\n"
          ]
        }
      ],
      "source": [
        "Stack_final_X_train = np.concatenate((lgb_train, xgb_train, rf_train), axis=1)\n",
        "Stack_final_X_test = np.concatenate((lgb_test, xgb_test, rf_test), axis=1)\n",
        "print('Original train feature Shape:',X_train.shape, 'Original test feature Shape:',X_test.shape)\n",
        "print('Stacking train feature Shape:', Stack_final_X_train.shape,\n",
        "      'Stacking test feature 데이터 Shape:',Stack_final_X_test.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0cose8uB8oYl",
        "outputId": "ff14f386-b77d-4760-fa88-96109e8f7df8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Final-Meta model F1-score: 0.6536\n",
            "Final-Meta model Accuracy score: 0.8264\n"
          ]
        }
      ],
      "source": [
        "xgb_final.fit(Stack_final_X_train, Y_train)\n",
        "stack_final = xgb_final.predict(Stack_final_X_test)\n",
        "\n",
        "print('Final-Meta model F1-score: {0:.4f}'.format(f1_score(Y_test, stack_final)))\n",
        "print('Final-Meta model Accuracy score: {0:.4f}'.format(accuracy_score(Y_test, stack_final)))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "phuWX_Bh8oYl"
      },
      "source": [
        "# Other Method"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "K0ls4kJK8oYl"
      },
      "outputs": [],
      "source": [
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.svm import SVC"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XBn62PWC8oYl",
        "outputId": "f1899348-e6be-488a-c259-9114332bcbcb"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.5171259962280221"
            ]
          },
          "execution_count": 24,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dt=DecisionTreeClassifier()\n",
        "dt.fit(X_train,Y_train)\n",
        "pred=dt.predict(X_test)\n",
        "f1_score(Y_test,pred)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YdJwWIZh8oYm",
        "outputId": "386a41e6-176d-445a-e0cf-bbad3c025fb6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.5345409886398527"
            ]
          },
          "execution_count": 25,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "lr=LogisticRegression()\n",
        "lr.fit(X_train,Y_train)\n",
        "pred=lr.predict(X_test)\n",
        "f1_score(Y_test,pred)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "A-nq44JA8oYm",
        "outputId": "e09f6035-5a49-483e-87e9-5af88e4685e4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.537026287420184"
            ]
          },
          "execution_count": 23,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "svm=SVC()\n",
        "svm.fit(X_train,Y_train)\n",
        "pred=svm.predict(X_test)\n",
        "f1_score(Y_test,pred)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.10.6 64-bit",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.6"
    },
    "toc": {
      "base_numbering": 1,
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": false,
      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
      "toc_cell": false,
      "toc_position": {
        "height": "calc(100% - 180px)",
        "left": "10px",
        "top": "150px",
        "width": "265px"
      },
      "toc_section_display": true,
      "toc_window_display": true
    },
    "vscode": {
      "interpreter": {
        "hash": "8d49d813f58f62aea4f04ac001ca02f2068ced68335826a2279d78dcca36d253"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}