California_Price.ipynb

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    "colab": {
      "name": "Week5-EndtoEnd.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qA2hZt_hMkcM",
        "colab_type": "text"
      },
      "source": [
        "# California Housing Prices Dataset\n",
        "\n",
        "As Labwork 5 assignment, I analysed California Housing Prices Dataset and tried to predict house prices based on given features. For this purpose, I used 2 different method for prediction. Firstly, I binned the house prices due to the polynomial distribution of house prices and used classification methods to predict groups. Secondly, I used 5 different regression algorithms to predict house prices with different pre-process steps. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "27BAsHFMK_y4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "afd094fb-6af7-48c1-a945-cb3532eb82d5"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import os\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "\n",
        "os.chdir(\"drive/My Drive/Colab Notebooks/\")\n",
        "data = pd.read_csv(\"housing.csv\")\n",
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "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>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "      <th>ocean_proximity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-122.23</td>\n",
              "      <td>37.88</td>\n",
              "      <td>41.0</td>\n",
              "      <td>880.0</td>\n",
              "      <td>129.0</td>\n",
              "      <td>322.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>8.3252</td>\n",
              "      <td>452600.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-122.22</td>\n",
              "      <td>37.86</td>\n",
              "      <td>21.0</td>\n",
              "      <td>7099.0</td>\n",
              "      <td>1106.0</td>\n",
              "      <td>2401.0</td>\n",
              "      <td>1138.0</td>\n",
              "      <td>8.3014</td>\n",
              "      <td>358500.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-122.24</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1467.0</td>\n",
              "      <td>190.0</td>\n",
              "      <td>496.0</td>\n",
              "      <td>177.0</td>\n",
              "      <td>7.2574</td>\n",
              "      <td>352100.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1274.0</td>\n",
              "      <td>235.0</td>\n",
              "      <td>558.0</td>\n",
              "      <td>219.0</td>\n",
              "      <td>5.6431</td>\n",
              "      <td>341300.0</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1627.0</td>\n",
              "      <td>280.0</td>\n",
              "      <td>565.0</td>\n",
              "      <td>259.0</td>\n",
              "      <td>3.8462</td>\n",
              "      <td>342200.0</td>\n",
              "      <td>NEAR BAY</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20635</th>\n",
              "      <td>-121.09</td>\n",
              "      <td>39.48</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1665.0</td>\n",
              "      <td>374.0</td>\n",
              "      <td>845.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>1.5603</td>\n",
              "      <td>78100.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20636</th>\n",
              "      <td>-121.21</td>\n",
              "      <td>39.49</td>\n",
              "      <td>18.0</td>\n",
              "      <td>697.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>356.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>2.5568</td>\n",
              "      <td>77100.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20637</th>\n",
              "      <td>-121.22</td>\n",
              "      <td>39.43</td>\n",
              "      <td>17.0</td>\n",
              "      <td>2254.0</td>\n",
              "      <td>485.0</td>\n",
              "      <td>1007.0</td>\n",
              "      <td>433.0</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>92300.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20638</th>\n",
              "      <td>-121.32</td>\n",
              "      <td>39.43</td>\n",
              "      <td>18.0</td>\n",
              "      <td>1860.0</td>\n",
              "      <td>409.0</td>\n",
              "      <td>741.0</td>\n",
              "      <td>349.0</td>\n",
              "      <td>1.8672</td>\n",
              "      <td>84700.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20639</th>\n",
              "      <td>-121.24</td>\n",
              "      <td>39.37</td>\n",
              "      <td>16.0</td>\n",
              "      <td>2785.0</td>\n",
              "      <td>616.0</td>\n",
              "      <td>1387.0</td>\n",
              "      <td>530.0</td>\n",
              "      <td>2.3886</td>\n",
              "      <td>89400.0</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20640 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       longitude  latitude  ...  median_house_value  ocean_proximity\n",
              "0        -122.23     37.88  ...            452600.0         NEAR BAY\n",
              "1        -122.22     37.86  ...            358500.0         NEAR BAY\n",
              "2        -122.24     37.85  ...            352100.0         NEAR BAY\n",
              "3        -122.25     37.85  ...            341300.0         NEAR BAY\n",
              "4        -122.25     37.85  ...            342200.0         NEAR BAY\n",
              "...          ...       ...  ...                 ...              ...\n",
              "20635    -121.09     39.48  ...             78100.0           INLAND\n",
              "20636    -121.21     39.49  ...             77100.0           INLAND\n",
              "20637    -121.22     39.43  ...             92300.0           INLAND\n",
              "20638    -121.32     39.43  ...             84700.0           INLAND\n",
              "20639    -121.24     39.37  ...             89400.0           INLAND\n",
              "\n",
              "[20640 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a6RhEKxLQrqS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AHgrODXHMgLg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 620
        },
        "outputId": "4a7028c7-5456-41c6-e02e-b0aa8ec2969d"
      },
      "source": [
        "display(data.shape)\n",
        "display(data.describe())\n",
        "display(data.info())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "(20640, 10)"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20433.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "      <td>20640.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>-119.569704</td>\n",
              "      <td>35.631861</td>\n",
              "      <td>28.639486</td>\n",
              "      <td>2635.763081</td>\n",
              "      <td>537.870553</td>\n",
              "      <td>1425.476744</td>\n",
              "      <td>499.539680</td>\n",
              "      <td>3.870671</td>\n",
              "      <td>206855.816909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.003532</td>\n",
              "      <td>2.135952</td>\n",
              "      <td>12.585558</td>\n",
              "      <td>2181.615252</td>\n",
              "      <td>421.385070</td>\n",
              "      <td>1132.462122</td>\n",
              "      <td>382.329753</td>\n",
              "      <td>1.899822</td>\n",
              "      <td>115395.615874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-124.350000</td>\n",
              "      <td>32.540000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.499900</td>\n",
              "      <td>14999.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-121.800000</td>\n",
              "      <td>33.930000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>1447.750000</td>\n",
              "      <td>296.000000</td>\n",
              "      <td>787.000000</td>\n",
              "      <td>280.000000</td>\n",
              "      <td>2.563400</td>\n",
              "      <td>119600.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-118.490000</td>\n",
              "      <td>34.260000</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>2127.000000</td>\n",
              "      <td>435.000000</td>\n",
              "      <td>1166.000000</td>\n",
              "      <td>409.000000</td>\n",
              "      <td>3.534800</td>\n",
              "      <td>179700.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>-118.010000</td>\n",
              "      <td>37.710000</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>3148.000000</td>\n",
              "      <td>647.000000</td>\n",
              "      <td>1725.000000</td>\n",
              "      <td>605.000000</td>\n",
              "      <td>4.743250</td>\n",
              "      <td>264725.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>-114.310000</td>\n",
              "      <td>41.950000</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>39320.000000</td>\n",
              "      <td>6445.000000</td>\n",
              "      <td>35682.000000</td>\n",
              "      <td>6082.000000</td>\n",
              "      <td>15.000100</td>\n",
              "      <td>500001.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          longitude      latitude  ...  median_income  median_house_value\n",
              "count  20640.000000  20640.000000  ...   20640.000000        20640.000000\n",
              "mean    -119.569704     35.631861  ...       3.870671       206855.816909\n",
              "std        2.003532      2.135952  ...       1.899822       115395.615874\n",
              "min     -124.350000     32.540000  ...       0.499900        14999.000000\n",
              "25%     -121.800000     33.930000  ...       2.563400       119600.000000\n",
              "50%     -118.490000     34.260000  ...       3.534800       179700.000000\n",
              "75%     -118.010000     37.710000  ...       4.743250       264725.000000\n",
              "max     -114.310000     41.950000  ...      15.000100       500001.000000\n",
              "\n",
              "[8 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20640 entries, 0 to 20639\n",
            "Data columns (total 10 columns):\n",
            " #   Column              Non-Null Count  Dtype  \n",
            "---  ------              --------------  -----  \n",
            " 0   longitude           20640 non-null  float64\n",
            " 1   latitude            20640 non-null  float64\n",
            " 2   housing_median_age  20640 non-null  float64\n",
            " 3   total_rooms         20640 non-null  float64\n",
            " 4   total_bedrooms      20433 non-null  float64\n",
            " 5   population          20640 non-null  float64\n",
            " 6   households          20640 non-null  float64\n",
            " 7   median_income       20640 non-null  float64\n",
            " 8   median_house_value  20640 non-null  float64\n",
            " 9   ocean_proximity     20640 non-null  object \n",
            "dtypes: float64(9), object(1)\n",
            "memory usage: 1.6+ MB\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "None"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0xYUi5APNEpG",
        "colab_type": "text"
      },
      "source": [
        "#Exploratory Data Analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RbA2tIsUMiNF",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "3b550dba-7f69-4fe0-d221-6074279c4f0d"
      },
      "source": [
        "pd.options.display.max_rows = 10\n",
        "pd.options.display.float_format = \"{:.3f}\".format\n",
        "from google.colab import widgets\n",
        "\n",
        "from IPython.core.display import display, HTML\n",
        "import base64\n",
        "!pip install facets-overview==1.0.0\n",
        "from facets_overview.feature_statistics_generator import FeatureStatisticsGenerator\n",
        "\n",
        "fsg = FeatureStatisticsGenerator()\n",
        "dataframes = [\n",
        "    {'table': data, 'name': 'Data'}]\n",
        "censusProto = fsg.ProtoFromDataFrames(dataframes)\n",
        "protostr = base64.b64encode(censusProto.SerializeToString()).decode(\"utf-8\")\n",
        "\n",
        "\n",
        "HTML_TEMPLATE = \"\"\"<script src=\"https://cdnjs.cloudflare.com/ajax/libs/webcomponentsjs/1.3.3/webcomponents-lite.js\"></script>\n",
        "        <link rel=\"import\" href=\"https://raw.githubusercontent.com/PAIR-code/facets/1.0.0/facets-dist/facets-jupyter.html\">\n",
        "        <facets-overview id=\"elem\"></facets-overview>\n",
        "        <script>\n",
        "          document.querySelector(\"#elem\").protoInput = \"{protostr}\";\n",
        "        </script>\"\"\"\n",
        "html = HTML_TEMPLATE.format(protostr=protostr)\n",
        "display(HTML(html))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting facets-overview==1.0.0\n",
            "  Downloading https://files.pythonhosted.org/packages/df/8a/0042de5450dbd9e7e0773de93fe84c999b5b078b1f60b4c19ac76b5dd889/facets_overview-1.0.0-py2.py3-none-any.whl\n",
            "Requirement already satisfied: pandas>=0.22.0 in /usr/local/lib/python3.6/dist-packages (from facets-overview==1.0.0) (1.0.5)\n",
            "Requirement already satisfied: numpy>=1.16.0 in /usr/local/lib/python3.6/dist-packages (from facets-overview==1.0.0) (1.18.5)\n",
            "Requirement already satisfied: protobuf>=3.7.0 in /usr/local/lib/python3.6/dist-packages (from facets-overview==1.0.0) (3.12.4)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.22.0->facets-overview==1.0.0) (2.8.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.22.0->facets-overview==1.0.0) (2018.9)\n",
            "Requirement already satisfied: six>=1.9 in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.7.0->facets-overview==1.0.0) (1.15.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.7.0->facets-overview==1.0.0) (49.2.0)\n",
            "Installing collected packages: facets-overview\n",
            "Successfully installed facets-overview-1.0.0\n"
          ],
          "name": "stdout"
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              "        </script>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S78X8FYRNQDC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 852
        },
        "outputId": "6cc2758b-6e8b-44a3-80ef-e93d9e2e3629"
      },
      "source": [
        "data.hist(bins=50, figsize=(20,13),color = 'deepskyblue')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x936 with 9 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UCY2rYO5W5Dd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "outputId": "29203dc6-7c87-46b4-edc4-8551c0c61ea5"
      },
      "source": [
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>median_house_value</th>\n",
              "      <th>ocean_proximity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-122.230</td>\n",
              "      <td>37.880</td>\n",
              "      <td>41.000</td>\n",
              "      <td>880.000</td>\n",
              "      <td>129.000</td>\n",
              "      <td>322.000</td>\n",
              "      <td>126.000</td>\n",
              "      <td>8.325</td>\n",
              "      <td>452600.000</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-122.220</td>\n",
              "      <td>37.860</td>\n",
              "      <td>21.000</td>\n",
              "      <td>7099.000</td>\n",
              "      <td>1106.000</td>\n",
              "      <td>2401.000</td>\n",
              "      <td>1138.000</td>\n",
              "      <td>8.301</td>\n",
              "      <td>358500.000</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-122.240</td>\n",
              "      <td>37.850</td>\n",
              "      <td>52.000</td>\n",
              "      <td>1467.000</td>\n",
              "      <td>190.000</td>\n",
              "      <td>496.000</td>\n",
              "      <td>177.000</td>\n",
              "      <td>7.257</td>\n",
              "      <td>352100.000</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-122.250</td>\n",
              "      <td>37.850</td>\n",
              "      <td>52.000</td>\n",
              "      <td>1274.000</td>\n",
              "      <td>235.000</td>\n",
              "      <td>558.000</td>\n",
              "      <td>219.000</td>\n",
              "      <td>5.643</td>\n",
              "      <td>341300.000</td>\n",
              "      <td>NEAR BAY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-122.250</td>\n",
              "      <td>37.850</td>\n",
              "      <td>52.000</td>\n",
              "      <td>1627.000</td>\n",
              "      <td>280.000</td>\n",
              "      <td>565.000</td>\n",
              "      <td>259.000</td>\n",
              "      <td>3.846</td>\n",
              "      <td>342200.000</td>\n",
              "      <td>NEAR BAY</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20635</th>\n",
              "      <td>-121.090</td>\n",
              "      <td>39.480</td>\n",
              "      <td>25.000</td>\n",
              "      <td>1665.000</td>\n",
              "      <td>374.000</td>\n",
              "      <td>845.000</td>\n",
              "      <td>330.000</td>\n",
              "      <td>1.560</td>\n",
              "      <td>78100.000</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20636</th>\n",
              "      <td>-121.210</td>\n",
              "      <td>39.490</td>\n",
              "      <td>18.000</td>\n",
              "      <td>697.000</td>\n",
              "      <td>150.000</td>\n",
              "      <td>356.000</td>\n",
              "      <td>114.000</td>\n",
              "      <td>2.557</td>\n",
              "      <td>77100.000</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20637</th>\n",
              "      <td>-121.220</td>\n",
              "      <td>39.430</td>\n",
              "      <td>17.000</td>\n",
              "      <td>2254.000</td>\n",
              "      <td>485.000</td>\n",
              "      <td>1007.000</td>\n",
              "      <td>433.000</td>\n",
              "      <td>1.700</td>\n",
              "      <td>92300.000</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20638</th>\n",
              "      <td>-121.320</td>\n",
              "      <td>39.430</td>\n",
              "      <td>18.000</td>\n",
              "      <td>1860.000</td>\n",
              "      <td>409.000</td>\n",
              "      <td>741.000</td>\n",
              "      <td>349.000</td>\n",
              "      <td>1.867</td>\n",
              "      <td>84700.000</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20639</th>\n",
              "      <td>-121.240</td>\n",
              "      <td>39.370</td>\n",
              "      <td>16.000</td>\n",
              "      <td>2785.000</td>\n",
              "      <td>616.000</td>\n",
              "      <td>1387.000</td>\n",
              "      <td>530.000</td>\n",
              "      <td>2.389</td>\n",
              "      <td>89400.000</td>\n",
              "      <td>INLAND</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20640 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       longitude  latitude  ...  median_house_value  ocean_proximity\n",
              "0       -122.230    37.880  ...          452600.000         NEAR BAY\n",
              "1       -122.220    37.860  ...          358500.000         NEAR BAY\n",
              "2       -122.240    37.850  ...          352100.000         NEAR BAY\n",
              "3       -122.250    37.850  ...          341300.000         NEAR BAY\n",
              "4       -122.250    37.850  ...          342200.000         NEAR BAY\n",
              "...          ...       ...  ...                 ...              ...\n",
              "20635   -121.090    39.480  ...           78100.000           INLAND\n",
              "20636   -121.210    39.490  ...           77100.000           INLAND\n",
              "20637   -121.220    39.430  ...           92300.000           INLAND\n",
              "20638   -121.320    39.430  ...           84700.000           INLAND\n",
              "20639   -121.240    39.370  ...           89400.000           INLAND\n",
              "\n",
              "[20640 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ykAD0jLKWNEg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 897
        },
        "outputId": "1ed16c8f-80b8-45bd-a8a8-f69ef0bc6656"
      },
      "source": [
        "plt.rcParams['figure.figsize'] = (20.0, 15.0)\n",
        "fig, ax = plt.subplots(3,3)\n",
        "ax[0,0].boxplot(data.longitude)\n",
        "ax[0,0].set_title('longitude')\n",
        "ax[1,0].boxplot(data.housing_median_age)\n",
        "ax[1,0].set_title('housing_median_age')\n",
        "ax[2,0].boxplot(data.latitude)\n",
        "ax[2,0].set_title('housing_median_age')\n",
        "ax[0,1].boxplot(data.total_rooms)\n",
        "ax[0,1].set_title('total_rooms')\n",
        "ax[1,1].boxplot(data.total_bedrooms)\n",
        "ax[1,1].set_title('total_bedrooms')\n",
        "ax[2,1].boxplot(data.population)\n",
        "ax[2,1].set_title('population')\n",
        "ax[0,2].boxplot(data.households)\n",
        "ax[0,2].set_title('households')\n",
        "ax[1,2].boxplot(data.median_income)\n",
        "ax[1,2].set_title('median_income')\n",
        "ax[2,2].boxplot(data.median_house_value)\n",
        "ax[2,2].set_title('median_house_value')\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'median_house_value')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 9 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MMinOpHRiTlt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 977
        },
        "outputId": "84643d17-78b1-4587-cd87-9477dca4e743"
      },
      "source": [
        "cor = data.corr()\n",
        "\n",
        "plt.figure(figsize=(14, 14))\n",
        "ax = sns.heatmap(\n",
        "    cor, \n",
        "    vmin=-1, vmax=1, center=0,\n",
        "    cmap=sns.diverging_palette(20, 220, n=200),\n",
        "    square=True, annot = True\n",
        ")\n",
        "ax.set_xticklabels(\n",
        "    ax.get_xticklabels(),\n",
        "    rotation=45,\n",
        "    horizontalalignment='right'\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0.5, 0, 'longitude'),\n",
              " Text(1.5, 0, 'latitude'),\n",
              " Text(2.5, 0, 'housing_median_age'),\n",
              " Text(3.5, 0, 'total_rooms'),\n",
              " Text(4.5, 0, 'total_bedrooms'),\n",
              " Text(5.5, 0, 'population'),\n",
              " Text(6.5, 0, 'households'),\n",
              " Text(7.5, 0, 'median_income'),\n",
              " Text(8.5, 0, 'median_house_value')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 177
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x1008 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q4za5iVAUXHk",
        "colab_type": "text"
      },
      "source": [
        "# Machine Learning Approach\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r-XgxmRVahn6",
        "colab_type": "text"
      },
      "source": [
        "## Preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_FHHQYc9awYo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.model_selection import  train_test_split\n",
        "from sklearn.ensemble import IsolationForest"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "idPe2H8HbUOM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def log_transform(s, reverse=False):\n",
        "    if reverse:\n",
        "        return np.exp(s)-1\n",
        "    else:\n",
        "        return np.log(s+1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bvRaXF36ZvM6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "outputId": "7ed8bace-bb31-4a98-e877-3b706d7ec8ac"
      },
      "source": [
        "#Dropping missing values\n",
        "data2 = data.dropna().reset_index(drop = True)\n",
        "\n",
        "# Encoding ocean_proximity column\n",
        "data2['<1H OCEAN'] = data.loc[:,\"ocean_proximity\"] == \"<1H OCEAN\"\n",
        "data2['INLAND'] = data.loc[:,\"ocean_proximity\"] == \"INLAND\"\n",
        "data2['NEAR OCEAN'] = data.loc[:,\"ocean_proximity\"] == \"NEAR OCEAN\"\n",
        "data2['NEAR BAY'] = data.loc[:,\"ocean_proximity\"] == \"NEAR BAY\"\n",
        "\n",
        "# Outlier detection and removing with Isolation Forest\n",
        "X = data2.drop([\"median_house_value\",\"ocean_proximity\"],axis=1)\n",
        "y = data2.median_house_value\n",
        "\n",
        "clf = IsolationForest(random_state=42, contamination=.1)\n",
        "clf.fit(X)\n",
        "y_pred_train = clf.predict(X)\n",
        "\n",
        "X_rem = X[np.where(y_pred_train == 1, True, False)]\n",
        "y_rem = y[X_rem.index]\n",
        "\n",
        "X_rem = X_rem.reset_index(drop=True) \n",
        "y_rem = y_rem.reset_index(drop=True) \n",
        "X_rem"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>longitude</th>\n",
              "      <th>latitude</th>\n",
              "      <th>housing_median_age</th>\n",
              "      <th>total_rooms</th>\n",
              "      <th>total_bedrooms</th>\n",
              "      <th>population</th>\n",
              "      <th>households</th>\n",
              "      <th>median_income</th>\n",
              "      <th>&lt;1H OCEAN</th>\n",
              "      <th>INLAND</th>\n",
              "      <th>NEAR OCEAN</th>\n",
              "      <th>NEAR BAY</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-122.24</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1467.0</td>\n",
              "      <td>190.0</td>\n",
              "      <td>496.0</td>\n",
              "      <td>177.0</td>\n",
              "      <td>7.2574</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1274.0</td>\n",
              "      <td>235.0</td>\n",
              "      <td>558.0</td>\n",
              "      <td>219.0</td>\n",
              "      <td>5.6431</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>1627.0</td>\n",
              "      <td>280.0</td>\n",
              "      <td>565.0</td>\n",
              "      <td>259.0</td>\n",
              "      <td>3.8462</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.85</td>\n",
              "      <td>52.0</td>\n",
              "      <td>919.0</td>\n",
              "      <td>213.0</td>\n",
              "      <td>413.0</td>\n",
              "      <td>193.0</td>\n",
              "      <td>4.0368</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-122.25</td>\n",
              "      <td>37.84</td>\n",
              "      <td>52.0</td>\n",
              "      <td>2535.0</td>\n",
              "      <td>489.0</td>\n",
              "      <td>1094.0</td>\n",
              "      <td>514.0</td>\n",
              "      <td>3.6591</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18384</th>\n",
              "      <td>-121.09</td>\n",
              "      <td>39.48</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1665.0</td>\n",
              "      <td>374.0</td>\n",
              "      <td>845.0</td>\n",
              "      <td>330.0</td>\n",
              "      <td>1.5603</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18385</th>\n",
              "      <td>-121.21</td>\n",
              "      <td>39.49</td>\n",
              "      <td>18.0</td>\n",
              "      <td>697.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>356.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>2.5568</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18386</th>\n",
              "      <td>-121.22</td>\n",
              "      <td>39.43</td>\n",
              "      <td>17.0</td>\n",
              "      <td>2254.0</td>\n",
              "      <td>485.0</td>\n",
              "      <td>1007.0</td>\n",
              "      <td>433.0</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18387</th>\n",
              "      <td>-121.32</td>\n",
              "      <td>39.43</td>\n",
              "      <td>18.0</td>\n",
              "      <td>1860.0</td>\n",
              "      <td>409.0</td>\n",
              "      <td>741.0</td>\n",
              "      <td>349.0</td>\n",
              "      <td>1.8672</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18388</th>\n",
              "      <td>-121.24</td>\n",
              "      <td>39.37</td>\n",
              "      <td>16.0</td>\n",
              "      <td>2785.0</td>\n",
              "      <td>616.0</td>\n",
              "      <td>1387.0</td>\n",
              "      <td>530.0</td>\n",
              "      <td>2.3886</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>18389 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       longitude  latitude  housing_median_age  ...  INLAND  NEAR OCEAN  NEAR BAY\n",
              "0        -122.24     37.85                52.0  ...   False       False      True\n",
              "1        -122.25     37.85                52.0  ...   False       False      True\n",
              "2        -122.25     37.85                52.0  ...   False       False      True\n",
              "3        -122.25     37.85                52.0  ...   False       False      True\n",
              "4        -122.25     37.84                52.0  ...   False       False      True\n",
              "...          ...       ...                 ...  ...     ...         ...       ...\n",
              "18384    -121.09     39.48                25.0  ...   False       False     False\n",
              "18385    -121.21     39.49                18.0  ...   False       False     False\n",
              "18386    -121.22     39.43                17.0  ...   False       False     False\n",
              "18387    -121.32     39.43                18.0  ...   False       False     False\n",
              "18388    -121.24     39.37                16.0  ...   False       False     False\n",
              "\n",
              "[18389 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ja9eFg8pbln8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "60f3b597-46e3-4aaa-9223-145d23d66a5c"
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X_rem, y_rem, test_size=0.33, random_state=42)\n",
        "\n",
        "reg = LinearRegression()\n",
        "reg.fit(X_train, y_train)\n",
        "reg.score(X_test, y_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6655300289909718"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DI3Zwwk5UdfJ",
        "colab_type": "text"
      },
      "source": [
        "## Bucketing Median House Value and Classification\n",
        "\n",
        "Due to the Polynomial Probability Distribution of the Median House Value column, we can try bucketing this column and convert numeric values into categoric groups based on theri quantiles. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IGdrXTvQOb_5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "outputId": "9d91880f-1490-4a9d-e77e-f2af3d4bb7a3"
      },
      "source": [
        "y_rem_b = pd.qcut(y_rem, 10, labels=False)\n",
        "y_rem_b = y_rem_b.astype('category',copy=False)\n",
        "y_rem_b"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        8\n",
              "1        8\n",
              "2        8\n",
              "3        7\n",
              "4        8\n",
              "        ..\n",
              "18384    0\n",
              "18385    0\n",
              "18386    1\n",
              "18387    1\n",
              "18388    1\n",
              "Name: median_house_value, Length: 18389, dtype: category\n",
              "Categories (10, int64): [0, 1, 2, 3, ..., 6, 7, 8, 9]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ESIgxiX7jAnS",
        "colab_type": "text"
      },
      "source": [
        "### Model Building"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0GCWRSxsRgZl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 106
        },
        "outputId": "b2f53cac-7938-4be0-e582-fe995b00adb7"
      },
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.model_selection import  train_test_split, cross_validate\n",
        "from sklearn.feature_selection import RFE, SelectKBest, chi2, SelectFromModel\n",
        "\n",
        "# Splitting\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X_rem, y_rem_b, test_size=0.15, random_state=42)\n",
        "\n",
        "# Feature Selection\n",
        "selector = SelectFromModel(RandomForestClassifier()).fit(X_train, y_train)\n",
        "\n",
        "X_rnd_train = selector.transform(X_train)\n",
        "X_rnd_test = selector.transform(X_test)\n",
        "\n",
        "rnd_features = X_rem.loc[:,selector.get_support()].columns.tolist()\n",
        "print(\"Selected Columns:\",rnd_features,\"\\n\")\n",
        "\n",
        "# Model Building\n",
        "rnd = RandomForestClassifier(random_state = 42)\n",
        "\n",
        "cv = cross_validate(rnd,X_rnd_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_rnd_test,y_test)))\n",
        "print(\"Accuracy Scores of cross valdations: {}\".format(cv['test_score']))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Selected Columns: ['longitude', 'latitude', 'housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income'] \n",
            "\n",
            "Mean training accuracy: 0.4394113883557262\n",
            "Test accuracy: 0.4697354113809351\n",
            "Accuracy Scores of cross valdations: [0.44107486 0.44069098 0.43646833]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9IOdEVAjTn3l",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "b69724e7-71dc-4c92-f5c1-c3ae34f773e4"
      },
      "source": [
        "fi_dt = pd.DataFrame({'Feature':rnd_features,\n",
        "       'Importance':cv[\"estimator\"][0].feature_importances_}).sort_values(by = \"Importance\",ascending = True).reset_index(drop = True)\n",
        "       \n",
        "fig = px.bar(fi_dt, x='Importance', y='Feature',orientation='h',color='Importance')\n",
        "fig.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AAWvoN5Zg13x",
        "colab_type": "text"
      },
      "source": [
        "### Hyperparameter Tuning"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jgbIh5AZg0rX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "outputId": "99134195-a862-424f-93e7-680ef9864625"
      },
      "source": [
        "from sklearn.model_selection import RandomizedSearchCV, GridSearchCV\n",
        "\n",
        "param_rnd = {\"min_samples_split\" : [2, 50, 150, 500],\n",
        "             \"criterion\" : [\"gini\",\"entropy\"],\n",
        "             \"ccp_alpha\": [0,1e-4,1e-3,0.01,0.1] }\n",
        "\n",
        "\n",
        "ran_forest = RandomForestClassifier(random_state = 42)\n",
        "\n",
        "clf_rnd = GridSearchCV(ran_forest, param_rnd, cv=3, n_jobs = -1)\n",
        "clf_rnd.fit(X_rnd_train, y_train)\n",
        "\n",
        "print(\"Tuned Random Forest Classification Parameters: {}\".format(clf_rnd.best_params_)) \n",
        "print(\"Mean of the cv scores is {:.6f}\".format(clf_rnd.best_score_))\n",
        "print(\"Test Score {:.6f}\".format(clf_rnd.score(X_rnd_test,y_test)))\n",
        "print(\"Seconds used for refitting the best model on the train dataset: {:.6f}\".format(clf_rnd.refit_time_))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tuned Random Forest Classification Parameters: {'ccp_alpha': 0.0001, 'criterion': 'gini', 'min_samples_split': 2}\n",
            "Mean of the cv scores is 0.442418\n",
            "Test Score 0.476260\n",
            "Seconds used for refitting the best model on the train dataset: 10.398756\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J1g7moQChhgy",
        "colab_type": "text"
      },
      "source": [
        "### Confusion Matrix"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dWHcAiDzS9vz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "04eba78a-b987-4082-b6b7-5c240398c591"
      },
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "\n",
        "y_pred = clf_rnd.predict(X_rnd_test)\n",
        "conf=confusion_matrix(y_test, y_pred)\n",
        "\n",
        "plt.figure(figsize=(20, 10))\n",
        "ax = sns.heatmap(conf, annot=True,cmap='Blues',fmt='g',annot_kws={\"size\": 13})\n",
        "ax.set_xlabel('Predicted Labels',fontsize = 15)\n",
        "ax.set_ylabel('True Labels',fontsize = 15)\n",
        "ax.set_title('Confusion Matrix',fontsize = 20)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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+fPct/f77r8rIyFDFipX0wEOPqOnVzd2OlqOwkPzxwTcnHo9HPbr9n1at+kPJycmKiYlRgwYN9fCjPVSxYiW34wWFQB7jkAB5HUtSZmam3n/3bU2ZNEFpaWm6vFFj9e3/kooXL+F2tBwVDlPgDPQ5uPKdJY59p13cq4nrY+lYwcEfAqngEKjya8EhmOTngkMwya8Fh2ASCAWHQJdfCw7BJJAKDoEsUAoOwOkEUsEhkAV7weGqd7937Dvtd080dn0suSA2AAAAAADwO/50AgAAAACAA/LJ1AqOocMBAAAAAAD4HR0OAAAAAAA4IL9cPcIpdDgAAAAAAAC/o8MBAAAAAAAHFLAGBzocAAAAAACA/9HhAAAAAACAA5jDAQAAAAAAIJcoOAAAAAAAAL/jlAoAAAAAABxQwM6ooMMBAAAAAAD4HwUHAAAAAAAcEGKMY0tOjDFfGGN2G2P+OG5df2PMNmPMSt/S+rhtzxpjNhhj1hpjrj+j53tOowQAAAAAAALZl5JaZrP+PWttPd8yQ5KMMXUkdZB0ge+YT4wxoTk9AAUHAAAAAAAcYIxzS06std9J2n+G0W+WNMpam2qt/VvSBkkNczqIggMAAAAAADjqUWPMb75TLor71sVJ2nLcPlt9606LggMAAAAAAA4wxji5dDXGLD9u6XoGET+VVE1SPUk7JL2Tm+fLZTEBAAAAAAgy1trBkgaf5TG7jv7bGPO5pGm+m9skVTxu1wq+dadFhwMAAAAAAA4IMc4t58IYU+64m7dKOnoFiymSOhhjChljqkqKl/RjTvdHhwMAAAAAAAWMMWakpGaSShljtkrqJ6mZMaaeJCtpk6SHJMla+6cxZoykVZIyJHWz1mbm9BgUHAAAAAAAcIA5k8tHOMRae2c2q/97mv1flfTq2TwGp1QAAAAAAAC/C6gOh9BzPREFZ6xoVLjbEYJeWCh1PgSHaWt35bwTcqVNzTJuRwh6hcND3Y5QIIREMM55jc/JQGDIRw0OjuCbDwAAAAAA8LuA6nAAAAAAACBQGRWsFgc6HAAAAAAAgN9RcAAAAAAAAH7HKRUAAAAAADigoM3vSocDAAAAAADwOzocAAAAAABwgClg18WkwwEAAAAAAPgdHQ4AAAAAADiggDU40OEAAAAAAAD8jw4HAAAAAAAcEFLAWhzocAAAAAAAAH5HhwMAAAAAAA4oYA0OZ9bhYIwpbYypetxtY4zpaox53xhzY97FAwAAAAAAgehMT6n4UlLP426/JOkTSS0lTTTG3OvfWAAAAAAABBdjjGNLfnCmBYdLJM2XJGNMiKT/k/SctbaWpFclPZ438QAAAAAAQCA604JDUUn7fP+uL6mEpOG+2/P/n737Do+iasM4/DtpkEBCCzWAtNCkCUhHRHqxIU1FLCCKKFL0ExVFRLGgYkFQxEbvvRepNgQFVJDee5Gavnu+PxKRSAuQ7GQ3z+01F7szs5uHcZnsvvueM0CJVM4lIiIiIiIi4lOM8dySHqS04LAPKJt0uwXwl7V2f9L9bEBMagcTEREREREREe+V0qtUfAW8a4xpSGLB4cULttUANqV2MBERERERERFf4pdeWg88JEUFB2vtW8aY/cCtwDMkFiD+kRMYkQbZRERERERERMRLpbTDAWvtSGDkJdY/maqJRERERERERMTrXbbgYIwJuZYnstZG3Xgc3zHk48HMmzubUydPEpQpE5WrVKX3833In7+A09G80qL5c5k8cSxbt2wmNiaG79f8fn7bDyuXM2bUN2zbuhm3y02xEiXo+nQPKlWu6mBi7zN8yAf89P0Kjh4+RHBICNVr3cbj3XoSli3bJfedMPpr+vQbSKNmdzqQ1rv9+dtqpoz8jH27dxAYFES1ug15uNv/AFi1ZC7Tx4zg1N/HKHhTCTp2e56ikWUcTpy+bf9lGRuXzebEvh0kxMXSadicZNv3/rGGnyd/wZljhwjLnZ/qbR6nYNkqFz3P8X07mTGwO/kiy9G851ueiu/13G43Lz7zGJv/3MCIifMIz5OXndu2MGr4x+zYupmTfx9n4MdfUrbCLU5H+PyEZAAAIABJREFU9TqLF8xl6qRxbNua+Ltv+c8bzm8b+dVwRn09PNn+0dHRtG73ID2ef8nTUX1Gv759mDd3NkGBQefXde/5HG3bP+BgKt8yf+4cJowfw5bNfxETE8Pa9RudjuSTXC4XHw1+j5nTpxEbG0vNWnV45bX+5MiR0+loGV7GGlBx5UkjzwJnrmGRC7RoeTfjJ01n1U9rmTN/Cfny5afP872cjuW1QsPCuK/N/fR8rs9F206fOU2b9g8yeeZ85n23isZNW9Lz6Sc4fOigA0m9l5+/Py++9hbTFq5k+KjJHD1yiHcH9L1ov7/+/J3VP64iV3huB1J6v00b1jJk4Is0u+9BPp2wkMEjZ1GvyV0AbPlzHd8OeYeHn/4fQycupmrt+nzQryfRUWcdTp2+ZQoJpWy9ltRo+8RF204fPcjiz96gYtN2dPxwMhWbtmXxsAGcOXY42X5ul4uV3w4mX4mbPRXbZ8ycNIZMmTInWxcQGECN2+6g71sfOZTKN4SGhXFv6/Z073Xx776Oj3Vh0co155cvR0/GGEPjZi0dSOpbWt55D6t+/vX8omJD6grLFkbb9g/w/AsqjKWlr0YMZ+l33zF63CQWfrcCgJf7/M/hVJIRXWlIxWOA9VQQX1O0WLF/71iLn58fu3ftdC6Ql6tRqw4Aa9esvmhb0+bJv2G/r217vhz+KRv//IO8+fJ7JJ8v6Nz12fO3s+fISat2HRjw8nPJ9omLi+O9ga/Ss08/3nzlBU9H9AmTvhlK/eatuLVOg/PripQoDcCy+TOoWut2yleuAUDz1h1YPHsSa39YTp2GLRzJ6w0K3pzYrXBg84aLtm39cTHhN5UgssYdAJSofgebVsxl64+LqXzng+f3Wz9/AuFFIgkOy8HhbX96JrgP2L93N/NmTOKF/oPo9fj959cXuqkYhW4qdoVHSkpUr5n4u+/XS/zu+6+Z0yYRWaoMZctVSOtYIjekVu26APyy+meHk/i2KZMm0qXrUxQsVAiAnr2fp2WzRhw4sJ8CBSIcTpexGU0amcha+01a/3BjzEhrbce0/jlOmTdnFgPf6M/Zs2cJCAig13P6gOYJ27Zu4dTJkxQvEel0FK/225qfKRZZKtm6kSOGUqlKdW4uX8mhVN4tNiaaHVs2Elm2Aq8+05HjRw9R8KbitO/UnaIly7B359ZkhQVjDDcVL8meHVsdTO3dTuzbSXjhEsnWhRcuwfF9O/7dZ/9OtvywiHv7DuH3xdM8HdFrud1uhrzTn0e79iBL1lCn42RocXFxzJs1nS7dnr36znJV3y1eyNIli8ieIzv1bm9Al67dCAnJ4nQskRQ7ffo0Bw8eoGzZcufXFSpcmKxZs7Llr79UcBCPSvGkkQDGmLJAFaAQ8JW19pAxpgRw2Fp7xWEVxpiZ/10F1DfGZAew1t51LVm8QbMWd9KsxZ0cO3aU6VOnEFmypNORfN6JE8d58blneeChRyl8UxGn43itFd8tYta0iXww9Ovz6zZv+pPl3y1k+MjJDibzbufOnsa63fy0fBG9Xx9MgYJFmDd1DO/368k7X0wiOiqK4JCsyR4TkiWU6KhzDiX2fvExUQQFJ/+gEBSchfiY3UDiUIoV3wymZrsnL9pPrmz2lLFkz5mLGnXv4PDBA07HydCWLVlIfEI8jZqqE+pGtX+gA917PkeOHDnZuWM7/V99iTdee4WB737gdDSRFIs6l/i+IWto8vcUoaFhnD2nYZpO88tYDQ5XnMPhPGNMVmPMROAPEi+BOQD4Z/bDgUC/FDxNQeA08AHwftJy5oLbPis8PDet7mtD925dOXXqpNNxfNbRI0fo9vgjVK9Zm6e693Q6jtdavmQBH7z9GgMGfULJ0mUBiI+PZ9Abfen+3MsEh1zTfLJygcxJH2jrNmxJ4aKRBAQG0rLtw7hcCWzbtIHgkJCL5muIOneGYH2zdt0CM4cQF528YBMXfY7AzImv4w0LJhGWtwCFK1R3Ip7XOrhvDzMmjKbLs+rcSw9mTJ1I46Yt9S18KihTthy5coXj5+dH8RKR9Hr+RRYvXkhcXJzT0URSLCRL4rng7Jnk7ynOnDlN1ixZL/UQkTSTooIDiUWCWkADIJTkk2vOBZqm4DmqAmuBl4FT1tplQLS1drm1dvnlHmSM6WKMWWOMWfPViOGX2y3dS3AlEB0dxdEjR5yO4pMOHNjPk50eombtujzXp2+GGxuVWubPnsbgd17njUFDuKVKtfPrjx89wq4d2xnYrw/3NqnLvU3qcvTIIT4a9AYDX9UHjpQKyZKV8Lz5+e/L02AAQ6Gikezatvn8emste7ZvpXAxDQ+6XjkLFuX4nu3J1h3fs51cBRPnF9i36Vf2/r6aUb3aMapXOzYsmMyhrX8wqlc7Ys5pPuTL2fj7Ok6d+pvuj7blobvuoHeXxEn1enRqx9zpEx1Ol7Hs3LGN9b+t5e772jodxSf5JX0Vaa2mNRPvERYWRv78Bdi06d85ifbt3cvZs2eJLFXqCo8UTzDGeGxJD1I6pKIV8Ky1dqkxxv8/23YDN13tCay1bmCwMWZS0p+HU/LzrbXDgeEAUXHecbZ3u91MHD+Wxk2akTNXLg4fOsQ7b71BgYgIihTVJFrXw+VykZCQQEJ8PACxsbEABAUFsXvXTp55shMt7rqHJzV+9bpNnTCGkV8O4+0PP6f0BWP+AHLnzce4GQuTrXumcwfadXiUO5qohfdaNGhxHwtnTKDG7Y3JF1GY+VPHERAYSGTZCgSHhPDeKz34c90vlLq5EgtnTiA+PpYqteo5HTtdc7tduF0u3K7E80NCfOI3kf4BgUTWbMCGhVPYvnoZRavUYefaVRzbs5V6jyZOiNqgy0u4E+LPP9fvi6ZxdPcW7uj8Apk0xOKy6tRvRMUq/3aFHD96mBe6PcJrg4YSUbgI1lriL/hGOCEhnrjYWPwDAvD3/+/bCLmc87/7Ei7+3ffPG8kZUydxc/mKRJYs7VhOX7Jg3hxq1a5LaFgYe3bvYvB771CvXn0yZcrkdDSf8c/rOv4S7+nSywckX3Bfm7Z8/eUX3FqtOtmz5+DDDwZRq3YdIiIKOh1NMpiUFhyCgeOX2RYKuFL6A621+4A2xpgWJA6x8EmrVq5g+OdDiY6OJjQ0lKpVq/HZF18TEHBN02ZIknlzZvJGv5fP369XI/F67lPnLGLUNyM4euQwE8aMZMKYkef3eaHvaxddwUIu79PBb+PvH0Dvbo8lWz9n6Wr8/f3JnSdfsvV+fv5kDQ0jW7bsnozp9Zrd14GY6CjeebEb8XFxFC5ekt6vf0hIlqyUvLkSHbv9j68/HsjJE8cpWKQ4vfoPvmheB0lu20/fseLbf8dXf/P03QC0e/MbwnIXoOGTffl58hesGDmY0PB8NOz6CqHheQEIDk3++g0MDsE/IJAsOXTZ1yvJlDmYTJmDz993uRLfBmTPmYvgkBAOHzzAE/f/e3nGV3s9CcAzL7xGg2Y+N2VTmlkwdyYD+/97eeIGtSsDMGnmQvIXiCA2Job5c2bybG91mqWWKZPG8/abrxMXF0fOnDmp36AhXbo+43QsnzJ71gz69X3x/P3qVRKvrDJnwRJ9GE5Fj3XuwunTp3mwXWvi4uKoUas2A98Z5HQsgYs6XX2dSUmLmDFmGXDAWvtAUodDPFDVWvurMWYkEG6tbZ62Ub2nw8GbxSa4nY7g887Fprg+Jzdg34kopyP4vJV7Tzgdwee1LJXX6Qg+Lzyrvrn2hOAgdbakNf+MNhOdAzLaB0WnZA7Ap4/0Q2PWe+wz7agHKzp+LFP6dfsrwCJjzGJgEmCB5saYnkBr4LY0yiciIiIiIiLiEzLa0KEUTRpprV1J4oSRmYAhJE4a2R8oBjS01v6SZglFRERERERExOukeEIBa+33QF1jTDCQAzhprVXPsoiIiIiIiEgKZLTRTym9LOaFYkicwyE6lbOIiIiIiIiIiI9IccHBGNPcGPMDiQWHQ0CMMeaHpKtNiIiIiIiIiMgVGGM8tqQHKSo4GGOeAGYBZ4FngTZJf54FZiZtFxEREREREREBUj6Hw0vA59bap/6z/jNjzGfAy8DnqZpMRERERERERLxWSodU5AKmXWbbFCBn6sQRERERERER8U3Gg0t6kNKCw1Kg3mW21QNWpE4cEREREREREfEFlx1SYYwpe8Hdj4ERxphcwHTgCJAHuBdoBnROy5AiIiIiIiIi3s4vnUzm6ClXmsPhD8BecN8ATyQtluRdGvMB/1RPJyIiIiIiIiJe6UoFh/oeSyEiIiIiIiLi4zJYg8PlCw7W2uWeDCIiIiIiIiIiviOll8U8zxjjB2T+73prbVSqJBIRERERERHxQSaDtTik6CoVJtELxphtQDxw5hKLiIiIiIiIiAiQ8stidgf6AF+SOFnkm8DrwBZgF9AlLcKJiIiIiIiI+ApjPLekByktODwO9APeTbo/3VrbH7gZ+AuITINsIiIiIiIiIuKlUlpwKAqss9a6SBxSkR3AWusGhgIPp008EREREREREd/gZ4zHlvQgpQWH40DWpNt7gFsu2JYDCE7NUCIiIiIiIiLi3VJ6lYrvgVuBucBY4DVjTE4gDugGLEmbeCIiIiIiIiK+IZ00HnhMSgsOrwERSbcHkjik4hESOxsWAc+kdjARERERERER8V4pKjhYazcDm5NuxwLPJi0iIiIiIiIikgImg7U4pHQOh8syxtxnjHGlRhgRERERERER8Q0pHVKRPmSsYpAj/P10kNNaWLB3/bPzVsXzZL36TnJDgoP8nY7g8xbvOOJ0BJ/XpHhepyNkCC53oNMRfF5IJp2T01qA3id7iG8f5xv+xt/LZLS/r4iIiIiIiIh4gAoOIiIiIiIiIpLq1NstIiIiIiIi4gEZbdLIyxYcjDETU/gcBVMpi4iIiIiIiIj4iCt1OORO4XPEAitSIYuIiIiIiIiIz8poc49etuBgra3vySAiIiIiIiIi4js0h4OIiIiIiIiIB2S0DgddpUJEREREREREUp06HEREREREREQ8IKNdpUIdDiIiIiIiIiKS6tThICIiIiIiIuIBmsPhCkyiQsaYWsaYLGkVSkRERERERES8W4oLDsaYp4D9wG5gJVAqaf1UY0yPtIknIiIiIiIi4huM8dySHqSo4GCMeR74APgCuAO4MP4yoF2qJxMRERERERERr5XSORy6Aa9aa981xvj/Z9tmoGTqxhIRERERERHxLX7ppfXAQ1I6pCIfsPYy29xA5tSJIyIiIiIiIiK+IKUFh21Avctsuw3YmDpxRERERERERHyTnweX9CClQyo+BIYaY+KAyUnr8hhjOgG9gMfTIpyIiIiIiIiIeKcUFRystSOMMTmAV4H+SavnAlHAa9basWmUT0RERERERES8UEo7HLDWDjLGfAbUAnIBJ4AfrbWn0iqciIiIiIiIiK/IYHNGprzgAGCtPQMsSKMsIiIiIiIiIuIjUlRwMMY8dbV9rLVDbzyOb/jog/dYsXwZhw8dJDgkhLq33c6zvXqTLVt2p6P5lGPHjvL+OwNZ88vPuBJclCpdhp7P96FkqdJOR/MZOsapb/GCuUydNI5tWzcTGxPD8p83nN828qvhjPp6eLL9o6Ojad3uQXo8/5Kno3o9t9vNqz06s2XjBoaNm0Ou3Hlxu1yM/epTvv9uAefOniF33vy06fg4NW5r6HRcrxN99jSrxg9n7x9rSYiP5aYK1ajXoRuZs4TidrtYO3s8G1ctJObMKcILF6deh26EFyrmdGyvMvKLISxfPI8zp08RFBTEzRUr06lbb/LkzY/L5WJU0vZzZ8+QJ18B7n+kC7Vvb+R0bK/x2Scf8OOq5Rw5cojg4BBq1L6NJ5/uRVi2bABs2/IXn3/6Ids2b+LEieN8MnwkFSpVdji1b9D7i7Q35OPBzJs7m1MnTxKUKROVq1Sl9/N9yJ+/gNPRMjxdFvPShlxh+SRpkSR+fn68+fa7LF31ExOmzODw4UO8+vKLTsfyOe+8+TqnT59iysx5LFi6kjI330zPZ7pirXU6ms/QMU59oWFh3Nu6Pd179bloW8fHurBo5Zrzy5ejJ2OMoXGzlg4k9X5zpowlU6bkV22eP3MSKxfP5ZV3P+Xbmctp92hXPhrYl/17djkT0ostHjGI+NhoOrz1JR3f+ZaYs6dZ9MUgANYtmMrmH7/jnufepvMnkyhQshwzP3iZuOgoh1N7l/qNW/Dxl+OZOG8VIybMIXeefAzqn3jumDNtAksXzmbAB58xYd4qHuz0FO8NeIm9u3c6nNp7+Pn78fLrbzNr0Sq+GjOFo0cO89brL5/fHhAYyG31G/LWB586mNI36f1F2mvR8m7GT5rOqp/WMmf+EvLly0+f53s5HUsyoBQVHKy1fv9dgJzA/cB6oGxahvQ2z/ToRekyZQkMDCRnzpw80KEja39Z7XQsn7Nv7x4aNGpKWFg2AgODuOve1hw5fIhTJ086Hc1n6Binvuo169CoaQsKRBS86r4zp00islQZypar4IFkvuXAvt0snDmJh554Ntn6Q/v3UrZCFQoUKoIxhmq1byc0LBt7d21zKKl3io+NYffva6h254MEBYeQOWsoVVu2Z/eG1Zw5foRta1ZS/o47yZYnP/4BgVS7+yFizp5hx68/OB3dqxS6qShZsoYm3rFg/PzYv3c3AAf376VcpaoULJz4Wq5Ztz6hYdnZs1Ov5ZTq8lQPSpYqQ0BAINlz5KR1+w6s+/WX89uLFC3Onfe0pnTZcg6m9E16f5H2ihYrRmjoP+cPi5+fH7t3qSCZHhjjuSU9uO7Lc1prT1prJwCfAZ9f6+ONMXWMMb2MMY2vN4O3WP3Tj2oRSwMPPfwYSxcv5O8TJ4iNjWXa5IlUuqUK2XPkcDqaz9Axdk5cXBzzZk3n7lZtnI7iddxuN8MGvc5DT/Qg5J8Pa0kaNr+Xvbu2s2/3DtwuFz+tWIzL5aJMebVJXwtrLViL5d9vI6078faxPdsTt130TaXl6N7tHkzpG5Ytmke75nVp07QWsyaP4/5HngCgSctW7Nm5nT27tuNyufh+2SJcrgRurljF4cTe69dffqJ4iVJOx8gQ9P7CM+bNmUXdmlWpVb0y48aM4omuTzsdSTKga5o08jJ2AlWvtpMxZrW1tlrS7ceBbsA0oJ8xprK19u1UyJLuLF60gMkTxzPim1FOR/E5FW6pzOxZ02lcvzb+/v7kzZuPj4YOv/oDJcV0jJ2zbMlC4hPiadS0hdNRvM7cqePInjMX1erU58ihA8m25ckfQenyt9C7czuM8SMwKJCnX3idbDlyOpTWOwVlDiaidAVWzxhNw069cScksHbOeADiYqIoUrE6v383iyIVq5E1Z25WTx+F2+0mXkMqrtntjZpxe6Nm/H38GAvnTqdIsUgA8hUoSNkKt/D0I20wfn4EBgbS6+U3yK7X8nVZ/t0iZkydyMeffeN0lAxB7y88o1mLO2nW4k6OHTvK9KlTiCxZ0ulIAvilk84DT7nuDgcAY0x+oDeJRYerCbzgdhegkbW2P9AYePAKP6OLMWaNMWbNVyO860S0aMF8BvR7lQ+HDKVM2ZudjuNT3G433bo8RuGbirD0+19Y+fOvPPr4Ezz+aAeOHz/mdDyfoGPsrBlTJ9K4aUtCQrI4HcWrHNq/l9mTx9Dpmf9dcvuIj99m17bNDBk9k7Hzf6TvO5/yxUdvsX7NTx5O6v0aPf4//AMCGfPy40x841mK3lITgMxZs1GleVuKVa7FjPdf4tvnHgIMOfMXInPWbM6G9mI5coXTpGUrXn+xO2dOn2LY4IHs2PoXI8bPZtri1Qx4fxhD33+TX3/50emoXmfp4gUMGtiPge8NoWRpjRJOa3p/4Xnh4blpdV8bunfryqlTGrYinpXSq1QcBf7bGxkEhAIxQKsUPI2fMSYHiUUOY609CmCtPWeMSbjcg6y1w4HhAFHx3jOTzIxpU/hg0Lt8NGQYlSqrVTe1nT51igP799Hu/g5kzZoVgHtatWHIh+/z+/p13H6HZpy/UTrGztm5Yxvrf1urK1Nch7/+WMfpU3/Tu3M7ANxJvzae63I/7R/pys6tm2hyV1ty580PQKmbK1K6XCV+W/09FavWcCy3N8qaI5ymXf99je5a/zP+gUHkK14a/8AgarftTO22nQGIPnOK9YunE1Fa85HcCJcrgZjoaE4cO8q2LZtocU9b8uRLnHG+TLlKlK1wC2t/WkXlW2s6nNR7zJ01jaEfDeKt94dQvqLer3mC3l84I8GVQHR0FEePHNGV8xymq1Rc2hDg0/8sbwEdgcLW2gUpeI5swFpgDZAzqTsCY0xWwKeO+tjRIxn83rsM/XyEig1pJHuOHBS+qQiTJ4wjOiqKhIQEZk6bwrlzUZQoqfGXqUHHOG24XC5iY2NJSIgHIDY2ltjY2GTj3WdMncTN5SsSWVJzv1yrmvUa8cnI6bz7+Vje/XwsL775EQB93x5CvcYtKHVzRVYumceJY0cA2LrpDzau/5VikTrW1+rvg3uJOXsG63ZzeOdmVo77nCrN25IpJCvnTp3g9LFDAJw5cZTFX75PvuJlKFxO8wuklNvtZvbU8Zz8+wQAx44c5rPBb5MnXwEKFi5CmXKVWLZ4HsePJr6WN2/8nT/WraV4yTJOxvYqkyeMZthH7zHo488vWWyw1p4/RwMkxMcTGxuLy+XydFSfovcXac/tdjN+7GhOHD8OwOFDh3j7zQEUiIigSFFdnlg8y1zt8jPGmECgGrDTWnvgijtfTwBjQoC81tqrDsvwlg6HW8qVJiAggMDAoGTrf/jlV4cSpVyCyysOMQA7d2zn4w8G8fvv60lISKBQocJ0fuIp6tVv4HQ0n+HNxzg23u10hEuaO2saA/v3vWj9pJkLyV8ggtiYGO5uVp9ne79As5b3OJAw5Q6cjHY6wlUdOXSApzvcxbBxc8iVOy9R584y+ouPWfvjSqKjzpEtR07qN72LVg885nTUS1qxJ/22F/+5fB4/Tx9JXHQUWbLnokKDu6jYKPE1e3jnFhZ+/jbnTh4nMHMwJarWpWbrxwjKHOxw6os1KZ7X6QiX5Ha7eb1Pd7Zt3khMTDRZsoZSvlJVHnysK/kjChF17ixff/Yhq39YQfS5c2TPmYuGze6m7UOdnI5+SWHBgVffycPqVSuHv38AQUHJs81fnnilioMH9tP+niYXPa7Pq2+ky/NzSCZ/pyOkmLe+vwjwksH3breb7t2eZOPGP4iOjiY0NJSqVavR9enuFCpU2Ol4VxUS5NstAAMWb/PYB65XGpZw/FimpODgB0QDzay133kk1WV4S8HBm3lTwUHkStJrwcGXeEPBwdul54KDr0ivBQdfkx4LDr7GmwoO3spbCg7eTgWH1JMeCg5XncPBWus2xmwF8nkgj4iIiIiIiIhPymh1q5TO4fAy8KoxpnxahhERERERERER33DZDgdjzG3Ar9bas0BfIBewzhizHzjMf65aYa2tlpZBRURERERERLyZ8a3rJVzVlYZULAVqAquBP5IWEREREREREZGrulLB4XzpxVr7qAeyiIiIiIiIiIiPuOqkkSIiIiIiIiJy4zLapJFXKzg0N8aUTskTWWtHpkIeEREREREREfEBVys4vJrC57GACg4iIiIiIiIil6EOh+TqA2s8EUREREREREREfMfVCg7R1tpzHkkiIiIiIiIi4sOMyVgtDn5OBxARERERERER36OrVIiIiIiIiIh4gOZwSGKtVfeDiIiIiIiIiFwXdTiIiIiIiIiIeEAGm8JBcziIiIiIiIiIZDTGmK+MMUeMMX9csC6nMWaRMWZr0p85ktYbY8zHxphtxpgNxpjKKfkZKjiIiIiIiIiIeICfMR5bUuAboOl/1vUBllhrI4ElSfcBmgGRSUsXYFiK/r4p2UlEREREREREfIe1dgVw4j+r7wa+Tbr9LXDPBetH2kQ/AdmNMfmv9jM0h4OIiIiIiIiIB3jBVSryWmsPJt0+BORNuh0B7L1gv31J6w5yBepwEBEREREREfExxpguxpg1FyxdruXx1loL2BvJoA4HEREREREREQ/w5FUqrLXDgeHX+LDDxpj81tqDSUMmjiSt3w8UumC/gknrrkgdDiIiIiIiIiICMBN4OOn2w8CMC9Z3TLpaRQ3g1AVDLy5LHQ4iIiIiIiIiGYwxZhxwOxBujNkH9APeBiYaYzoBu4G2SbvPBZoD24Ao4NGU/AzvKjjc0OgRSYkAL5jFxNu53Hohe0KAv17LaS1/9sxOR/B5t8blcDqCz5vx1yGnI2QIlfOFOR3B55WPyOZ0BJ8XHOTvdIQMwrffw/mlo7+ftfb+y2xqcIl9LdDtWn+GhlSIiIiIiIiISKrzrg4HERERERERES/lyUkj0wN1OIiIiIiIiIhIqlOHg4iIiIiIiIgHZLQp89ThICIiIiIiIiKpTh0OIiIiIiIiIh7gl8EmcVCHg4iIiIiIiIikOnU4iIiIiIiIiHhABmtwUIeDiIiIiIiIiKQ+dTiIiIiIiIiIeIDmcBARERERERERuUHqcBARERERERHxgAzW4KAOBxERERERERFJfepwEBEREREREfGAjPaNf0b7+4qIiIiIiIiIB6jgICIiIiIiIiKpTkMqRERERERERDzAZLBZI9XhICIiIiIiIiKpTh0OIiIiIiIiIh6Qsfob1OEgIiIiIiIiImlAHQ4iIiIiIiIiHuCXweZwUMEhjQz5eDDz5s7m1MmTBGXKROUqVen9fB/y5y/gdDSfoWOcttre25KDBw+ev+92u4iNjWX0+MmULnOzg8m826L5c5k8cSxbt2wmNiaG79f8fn7bkSOHGTTwdbZu/otDhw7S7423adbiLgfTeqfFC+YybdJ4tm1NPMbLfl6fbPu4UV8zffIE/v77BLlyhdP2gY7c26a9Q2m925+/rWbKyM/Yt3sHgUFBVKvbkIe7/Q+AVUvmMn3MCE6kLHvQAAAgAElEQVT9fYyCN5WgY7fnKRpZxuHE6dv2X5axcdlsTuzbQUJcLJ2GzUm2fe8fa/h58hecOXaIsNz5qd7mcQqWrXLR8xzft5MZA7uTL7IczXu+5an4Xuuvdb8wc8xwDu7ZSUBgEJXr3MH9Tz6H2+Vi/uSR/Lh4DmdPn6RgsUjaPdGbgkVKOB3Zq+ic7Jyff/qBYZ98xPZt2wjKFESjxk3p07ef07Ekg1HBIY20aHk3Dz/amdDQUKKjo/n0kw/p83wvvh093uloPkPHOG1NnDY72f1PP/mQ5d8tVrHhBoWGhXFfm/uJjY3h7TdeS7bNz/hRvWZtOjzSiVf6POdIPl8QGpaNe1u3JzY2hkED+yfbtmr5Ur76fCgfDhvBzeUr8seGdfR86nEKFirMrTVqOZTYO23asJYhA1/ksWdfolL1ulhrObBnJwBb/lzHt0Peofsr71C6fGUWTp/AB/168u6IyQSHZHU4efqVKSSUsvVakhAfy6rRHyfbdvroQRZ/9gZ1OnSnWNW67Fy7ksXDBnBfv88JDc97fj+3y8XKbweTr4TO1Smx5fdf+eLdvjzYrQ/lq9UGazm4dxcAS2aMZ/WyBTw74COy58rDnPFfMuS1Xrw2dByZQ7I4G9yL6JzsjDW/rOaF3j3o228At91eH2stO7dvczqWoDkcJJUULVaM0NDQxDvW4ufnx+5dO50N5WN0jD0nISGBmdOn0Kp1O6ejeL0aterQuFkLChQsdNG28Ny5ad3uASpWqoyfn07P16t6zdo0bNqcAhEFL9q2b+8eSpQsyc3lKwJQrkIlikeWZNvWzZ6O6fUmfTOU+s1bcWudBgQGBhEUlIkiJUoDsGz+DKrWup3ylWsQGBhE89YdCAgMYu0Pyx1Onb4VvLkKxavdTmh4/ou2bf1xMeE3lSCyxh34BwRSovod5Cpcgq0/Lk623/r5EwgvEkneyHKeiu3VZoz6jLpN7qFy7foEBgYRGJSJwsVLAfDrD0u5rXkrwvNFEBAYSMv7O3PuzCnW/bTC4dTeRedkZ3z60Qfc16YdDRs3ISgoiEyZMlG6rAqR4nkee0drjKlujAlLuh1sjOlvjJlljHnHGJPNUzk8ad6cWdStWZVa1Sszbswonuj6tNORfI6OsWcsW7qEs2fP0uLOu52OInJDGjZpxrmz59iw7lfcbjfrf1vL3j27qF6zjtPRvEpsTDQ7tmzE5Urg1Wc60q19Y956oSs7t2wCYO/OrRSJLH1+f2MMNxUvyZ4dW52K7PVO7NtJeOHkrfzhhUtwfN+Of/fZv5MtPyyiWqvHPB3PK8XGRLNr6yZcbhdv9XyU5zs0Z/DLT7N7a+Lr2FoL1iZ7jLWWfTv1Ok4tOienjeioKP7843dcCS4ebNuKBrfVpMtjHdn45x9ORxPAGM8t6YEnh1R8BVRMuv0REAW8AzQAvgZaeTCLRzRrcSfNWtzJsWNHmT51CpElSzodyefoGHvG1MkTaNy4GaFhYU5HEbkh2XPk5PYGjXj2yccSP0wAz/R6gWIlIh1O5l3OnT2Ndbv5afkier8+mAIFizBv6hje79eTd76YRHRU1EVDJ0KyhBIddc6hxN4vPiaKoODkbfxBwVmIj9kNJA6lWPHNYGq2e/Ki/eTSos6ewbrdrFmxiG793idfxE0snj6WTwc8x2tDx1P+1tosnzuVclVrkSM8D7PHfYl1u4nR6zjV6JycNk6fPo3b7WbB/Dl8PHQ4RYoWZdQ3X/PsU08wddY8vZ8Tj/Jkz66ftTYh6XZVa20Pa+0qa21/oJgHc3hceHhuWt3Xhu7dunLq1Emn4/gkHeO0s2/vHn75+Sfua6PhFOL9vv3yMxYtmMtXY6ew9Kd1fD12ChPHjmT29ClOR/MqmZM+0NZt2JLCRSMT283bPozLlcC2TRsIDgkhOupsssdEnTtDsMa9X7fAzCHERSf/oBsXfY7AzCEAbFgwibC8BShcoboT8bxS5uDEY1ezQQsKFilBQGAgTVp3xJXgYsdfv9P4vg5UrHEbn/TrycudW2Ew5Ct4E1nDsjuc3HfonJw2smRJPNfeefe9RJYsRWBgEI927kJCQgLr1//mcDoxxnhsSQ88WXD4wxjzaNLt9caYqgDGmJJA/OUeZIzpYoxZY4xZ89WI4Z7ImSYSXAlER0dx9MgRp6P4LB3jtDFl8gQiS5amXIWKV99ZJJ3bvGkjt93egKLFimOMoWjxEtS9vQHfr9TcAtciJEtWwvPmv6hd02AAQ6Gikeza9u8YbGste7ZvpXAxfWt5vXIWLMrxPduTrTu+Zzu5CiZ+Z7Nv06/s/X01o3q1Y1SvdmxYMJlDW/9gVK92xJw740TkdC84S1Zy5bnE69gkfiAIDAyi1SPdGPDFZN4dOYeG997PscMHiCx/izOBfZDOyWkja2goBQpEXPSB0xiTdJ4W8RxPFhw6A/WMMduBssCPxpgdwBdJ2y7JWjvcWlvVWlv1sc5dPBT1xrjdbsaPHc2J48cBOHzoEG+/OYACEREUKerTzRweo2PsGfHxccyeMV3dDanI5Uq8vGhCfGKdNTY2ltjY2POtpP/cx1pcCQmJ+yYkXOkp5T/+OcbxCRcf4/IVb2Hlsu/YuyexDX3Xzu2sXLaEUmXKOhnZKzVocR8rF81m/54duFwJzJ08moDAQCLLVuD2pnez9odl/LnuFxLi45k3dQzx8bFUqVXP6djpmtvtIiE+Drcr8bWbEB9HQnwc1loiazbg6O6tbF+9DLcrge2rl3Fsz1YiazYEoEGXl2j92ue0emUIrV4ZQpnbmpO7aClavTKETBpicVm3NbuXH5fM5eCenbhcCSyaNpaAwCCKlS7Pqb+Pc/xw4uWhTxw9zMiP3qRoqXKUvUVdJNdC52RntG53P7OmT2PH9m0kJCQw8usvCQwKpGIlFcyc5ufBJT0w9j+T4aT5D0ycOLIoifNH7LPWHk7pY6PiPBz2Orndbrp3e5KNG/8gOjqa0NBQqlatRtenu1OoUGGn4/kEbz7GLrdXvIwBWDBvDgMH9GPe4uWEeFkrdEI6Pc6zZ07jjX4vX7R+6pxFFCgQQY1bLn6T1emJp3j8yfQ3IWq8y+10hEuaO2s6b/Xve9H6iTMXkDtPXkYM+4QlC+dx6uTfhIZlo37DJjz5TA8CAgIdSHtlO46k37Hi1lqmjR7OsvnTiY+Lo3DxkjzweE9uKp44l86qJXOZPuYLTp44TsEixXm42/8oGlnG4dQXW7n3hNMRztvywyJWfPvBRevbvfkNoeF52fvHGn6e/AVnjh0iNDwfNdp2oWDZKpd8rrWzRnN425807/lWGqdOmcr50ueYcWsts8eO4PuFM4mPj6Ng0Uhad+pOoWIl2b11E1+9/xonjx8lc3AIlWvX5+6OXc8PxUhvykekzznYfemcHBzk73SEFLPW8vnQT5g2eRKxcbGUKl2GXs/3oVTp9Hce/q/QTH4+3YYx4bf9HnuT2u6WCMePpccLDjfCWwoOIlfiTQUHb5ZeCw6+JL0WHHxJei44+Ir0VHDwZem14OBL0mvBwZd4U8HBm/l6wWHiugMee5PatlIBx49leum0EBEREREREREfooKDiIiIiIiIiKS6AKcDiIiIiIiIiGQEjo9x8DB1OIiIiIiIiIhIqlOHg4iIiIiIiIgHGJOxehzU4SAiIiIiIiIiqU4dDiIiIiIiIiIekNG+8c9of18RERERERER8QB1OIiIiIiIiIh4gOZwEBERERERERG5QepwEBEREREREfGAjNXfoA4HEREREREREUkD6nAQERERERER8YAMNoWDOhxEREREREREJPWpw0FERERERETEA/wy2CwO6nAQERERERERkVSnDgcRERERERERD9AcDiIiIiIiIiIiN0gFBxERERERERFJdRpSISIiIiIiIuIBRpNGioiIiIiIiIjcGHU4iIiIiIiIiHhARps00qsKDn5+Gez/jgOsdTqB7/NXX5FH6HwhviBf9sxOR/B5TTPlcTpChrD24AmnI/i+/U4H8H0VIrI7HSFDCM2kN8u+xKsKDiIiIiIiIiLeyk9zOIiIiIiIiIiI3Bh1OIiIiIiIiIh4QEabw0EdDiIiIiIiIiKS6tThICIiIiIiIuIB6nAQEREREREREblB6nAQERERERER8QCjq1SIiIiIiIiIiNwYdTiIiIiIiIiIeIBfxmpwUIeDiIiIiIiIiKQ+dTiIiIiIiIiIeIDmcBARERERERERuUEqOIiIiIiIiIhIqtOQChEREREREREPMBlrRIU6HEREREREREQk9anDQURERERERMQDNGmkiIiIiIiIiMgNUoeDiIiIiIiIiAf4ZawGB3U4iIiIiIiIiEjqU4eDiIiIiIiIiAdoDgcRERERERERkRukDoc04nK5+Gjwe8ycPo3Y2Fhq1qrDK6/1J0eOnE5H8wnz585hwvgxbNn8FzExMaxdv9HpSD5pyMeDmTd3NqdOniQoUyYqV6lK7+f7kD9/Aaej+Ry3281jHR9gw/p1zFu0jLz58jkdyWstmj+XyRPHsnXLZmJjYvh+ze/ntx05cphBA19n6+a/OHToIP3eeJtmLe5yMK13GvHpYH7+YQXHDh8mc0gI1WrWpVO3HoSFZQMSfweOHzmCBbOnc+rk3xQvWZqne79EsRIlHU7undxuN32f7cSWjRv4fPxccuXOC8ChA3sZ+dmH/LHuFwAiChdlwIcjCAgIdDKuV4k6c5olYz5j5+9rSIiLpXil6jR+5BmCs4RyePd2lk34ksO7t3Hu1N90eGUwhUqVczqy1/pr3S/MHDOcg3t2EhAYROU6d3D/k8/hdrmYP3kkPy6ew9nTJylYLJJ2T/SmYJESTkf2GosXzGXqpHFs25r4e2/5zxvObxv51XBGfT082f7R0dG0bvcgPZ5/ydNRBTAZq8FBHQ5p5asRw1n63XeMHjeJhd+tAODlPv9zOJXvCMsWRtv2D/D8CzpRpqUWLe9m/KTprPppLXPmLyFfvvz0eb6X07F80phR35A5c7DTMXxCaFgY97W5n57P9blom5/xo3rN2vR/axB58qqoc738/P154dWBTJq/nGHfTuTY0cO8/8Yr57dPHT+K7xbM4Z2Pv2Dy/JWUq1iZl3t2JercOQdTe6/Zk8eQKXPmZOtOnfybV3p05qbiJRk2dg5fT1tKp2dewM/P36GU3mn2Z+8QHxvNE+99Q9fBo4g+e5pZw94BwD8ggFK31qFN7wEOp/R+W37/lS/e7UvDex7g3dFzGfjVNGo3uhOAJTPGs3rZAp4d8BGDRs+jRNmKDHmtFzFROl+kVGhYGPe2bk/3Xhf/3uv4WBcWrVxzfvly9GSMMTRu1tKBpJIRqeCQRqZMmsijnTpTsFAhQkND6dn7eb5ftZIDB/Y7Hc0n1Kpdl2bNWxJRsJDTUXxa0WLFCA0NTbxjLX5+fuzetdPZUD5o966dTBo/jp7PqSiZGmrUqkPjZi0ocInzQ3ju3LRu9wAVK1XGz0+/Aq/XY092p0SpMgQEBJI9R07uafsgG35dc377iu8W0vLeduSPKEhgYCAdO3fl9KmTfL/iOwdTe6cDe3ezYOYkOj7RI9n62ZNHE54nH+0efoIsWUPx9/enRKmyel1fg7iYaLZv+IXa93QgU3AIwVnDqHXX/Wxf9zOnjh0hPOImKtVvTv5ipZyO6vVmjPqMuk3uoXLt+gQGBhEYlInCxROP668/LOW25q0IzxdBQGAgLe/vzLkzp1j30wqHU3uP6jXr0KhpCwpEFLzqvjOnTSKyVBnKlqvggWRyKcaDS3rgsd9KxpjuxpgM8enw9OnTHDx4gLJl/227K1S4MFmzZmXLX385mEzk2s2bM4u6NatSq3plxo0ZxRNdn3Y6kk9xu930f/Vlejz3v3+LOyJeZt2anykaecFwCQsWm2wfa2HHFv0OvBZut5uh7/Wn45M9yJI1+fnhj3VryJU7LwNf6s4j99SnV+d2rFg816GkXsxauOC1am3i7SO7tzkUyPfExkSza+smXG4Xb/V8lOc7NGfwy0+ze+smIOmY2/+eLyz7dm51Iq5Pi4uLY96s6dzdqo3TUSQD8WQZfADwszFmpTHmKWNMbg/+bI/6p2U0a2jWZOtDQ8M4e+6sE5FErluzFney8sc1LFq6kie6Pk1kSY3BTk1jR48kV3g4dzRo5HQUkeuyculi5kyfRNceL5xfV732bcyaMoH9e3cTFxvLN58Pwe12EaUW6WsyZ+o4sucIp3qdOy7adubUSVavWkr9Jnfx5ZRFPPxkT4a9N4BNv//mQFLvFJQ5mMJlKrJy6ihizp0l6vRJfpg5DoDY6CiH0/mOqLNnsG43a1Ys4qFnX+atr2dQptKtfDrgOaLOnqH8rbVZPncqRw7sJT4ulpljhmPdbg2pSAPLliwkPiGeRk1bOB0lQ/MzxmNLeuDJgsMOoCCJhYcqwEZjzHxjzMPGGJ/6Wi8kSxYAzp5JXlw4c+Y0WbNkvdRDRNK98PDctLqvDd27deXUqZNOx/EJe/bsZvS3X/PCS69cfWeRdGjFdwv58O3+vPbOR0SWKnN+fduHHqN2vTt4sceTdLi3CcYYChUpSli27A6m9S4H9+9l1qTRdOp+6aFWmUOyULJseWrWa4i/fwAVq9ag0q01WfOD2tCvxV1d+xAQEMjw/3Xim37PEFm5JgDBodkcTuY7MgeHAFCzQQsKFilBQGAgTVp3xJXgYsdfv9P4vg5UrHEbn/TrycudW2Ew5Ct4E1nDdL5IbTOmTqRx05aEhGRxOopkIJ68SoW11rqBhcBCY0wg0Ay4H3gPuGTHgzGmC9AFYMjQz+n0eBcPxb1+YWFh5M9fgE2b/qR0mcQ3YPv27uXs2bNEltI4QPFeCa4EoqOjOHrkCNn0weGGrft1LX//fYK29yZOnOV2J7aUtrvvbp565lnatn/AyXgiV7Rg9nSGf/I+rw/6mJsr3JJsW1BQEJ279aRzt55A4gSH0yeOpULlW52I6pX++v03Tp/6m16d2gL/tvr3frw97R/tStHiJTm4f+/FD0wn32h5i9Cc4dzzTN/z97f99jMBgUFElChzhUfJtQjOkpVcefJf9NI0BowxBAYG0eqRbrR6pBsAZ0+fZOnsiUSWv+USzybXa+eObaz/ba2uTJEOZLSztCcLDsmOrbU2HpgJzDTGhFzuQdba4cBwgJiE/wwITcfua9OWr7/8glurVSd79hx8+MEgatWuQ0QKJnORq3O5XCQkJBAfHw9AbGwskPgm1+jNVqpwu91MHD+Wxk2akTNXLg4fOsQ7b71BgYgIihQt5nQ8n9CoSTOq16h1/v7hw4d4pEN7hg4foWN8A/45PyRc5vzwz32sxZWQQGxsLP7+/gQE6ErRKTV94hhGf/U5AwcPo1TZiy8TeOL4MeLiYsmXP4Ijhw/xyaA3KFOuAlWr17rEs8ml1Lq9ERWqVD9///jRI7z0zCP0fedTIgoXoVhkGV7p0YnVq5ZStVY9Nq5fy/q1P3FP+0ecC+2Fjh/YS0hYNjKHZOXgzq0sHj2UGne2J3OWrFhrcSWdRwBcCfEkxMXhF+Cvq4Fco9ua3cvS2ZOoWrcReSIKsWTGBAICgyhWujyn/j5OQlwcufLm58TRw4z/7D2KlipH2VuqX/2JBbjg917C5d8Xz5g6iZvLVySyZGnHckrGZKz1zGd4Y0xJa+2WG3kObyo4uFwuPvzgPWZOn0pcXBw1atXm1ddeJ0eOnE5HuyIPvRxu2IzpU+nX98WL1s9ZsCTdF3U89W/uRrndbrp3e5KNG/8gOjqa0NBQqlatRtenu1OoUGGn412Vdxzl5A7s30fLpg2Zt2gZefOl/0s2xiW4nY5wSbNnTuONfi9ftH7qnEUUKBBBjVvKXrSt0xNP8fiT6W9C1FPR8VffyQFNalXE3z+AwKDAZOtnLPkJgC2b/uStfn04fvQIwSEh1L2jEZ269iA45LLfLzjmTHSC0xFS5MihAzz14J18Pn4uuXLnBeCH5YsY/9Uwjh87TJ58EbTp+Di16qXP+WDWHjzhdIRLWrd0Lismf0ts9DlCc+SiSqO7ubVpKwBOHj3EsJ4PXfSYFl2eo8JtTTwd9aoKhaa/f1//sNYye+wIvl84k/j4OAoWjaR1p+4UKlaS3Vs38dX7r3Hy+FEyB4dQuXZ97u7Y9fxQjPSkQkT67O6cO2saA/v3vWj9pJkLyV8ggtiYGO5uVp9ne79As5b3OJDw2uQODfDpbw9/2nbSY29Ta5TI7vix9FjBITV4U8HBW3nRy8FredO/OW+mo5z20mvBwZek14KDL/GWgoO3S68FB1+SngsOviK9Fhx8jc8XHLZ7sOBQ3PmCgy7WLCIiIiIiIiKpTgNWRURERERERDzAZLBpI9XhICIiIiIiIiKpTh0OIiIiIiIiIh6Q0S6opw4HEREREREREUl16nAQERERERER8YAM1uCgDgcRERERERERSX3qcBARERERERHxhAzW4qAOBxERERERERFJdepwEBEREREREfEAk8FaHNThICIiIiIiIiKpTh0OIiIiIiIiIh5gMlaDgzocRERERERERCT1qcNBRERERERExAMyWIODOhxEREREREREJPWp4CAiIiIiIiIiqU5DKkREREREREQ8IYONqVDBQURERERERCQDMsbsAs4ALiDBWlvVGJMTmAAUAXYBba21f1/P82tIhYiIiIiIiIgHGA/+dw3qW2srWWurJt3vAyyx1kYCS5LuXxcVHERERERERETkH3cD3ybd/ha453qfSAUHEREREREREQ8wxnNLCllgoTFmrTGmS9K6vNbag0m3DwF5r/fvqzkcRERERERERHxMUgGhywWrhltrh/9ntzrW2v3GmDzAImPMXxdutNZaY4y93gwqOIiIiIiIiIh4gCcvUpFUXPhvgeG/++xP+vOIMWYaUA04bIzJb609aIzJDxy53gxeVXCw111XkZS6htYbuU56GXuGv17MaS7QX6Py0lqWTF71a9or6Rh7xi02h9MRfN7Qn/c4HcHnZfL3dzpChpA7VOcLTzHGZAH8rLVnkm43Bl4HZgIPA28n/Tnjen+GfsuKiIiIiIiIeEL6+k4sLzDNJH5RFwCMtdbON8b8Akw0xnQCdgNtr/cHqOAgIiIiIiIiksFYa3cAFS+x/jjQIDV+hgoOIiIiIiIiIh5g0lmLQ1rTAFwRERERERERSXXqcBARERERERHxgIw2r7k6HEREREREREQk1anDQURERERERMQDMliDgzocRERERERERCT1qcNBRERERERExBMyWIuDOhxEREREREREJNWp4CAiIiIiIiIiqU5DKkREREREREQ8wGSwMRXqcBARERERERGRVKcOBxEREREREREPMBmrwUEdDiIiIiIiIiKS+tThICIiIiIiIuIBGazBQR0OIiIiIiIiIpL61OEgIiIiIiIi4gkZrMVBHQ4iIiIiIiIikurU4SAiIiIiIiLiASaDtTiow0FEREREREREUp06HNLA/LlzmDB+DFs2/0VMTAxr1290OpJPcrlcfDT4PWZOn0ZsbCw1a9Xhldf6kyNHTqej+YSPPniPFcuXcfjQQYJDQqh72+0826s32bJldzqaT9HrOO3169uHeXNnExQYdH5d957P0bb9Aw6m8m6LF8xl6sRxbNu6mdiYGJav3pBs+98njvPph+/xw6rlJCQkUCCiIO99/BnhufM4lNg76Th7jtvt5tUendmycQPDxs0h1//bu+/4qMq0jeO/O4USktBFqqB0sVfKCtgpKuqCiGtFESuIooioYFlXRBd3bSCoKCAKiCIgRcG6Il2lw6vUUASBJJSUyfP+MQOmgIDMzMnMXF8/+SRzzpmZ6zwOyZx77vOcylXI8/kY/darfDdzGrszM6hcpSodb7qD8y+42Ou4xdrZNVJpVbcCNcqWokR8HHd/9Mf74CbHJ3NJ/YrUKFsKMyMtfR8fL97K6m17DmwTZ9CuUWWanlCO5JIJpO/L5f1Fm1iyOdOL3YkoSxfNYcJ7Q9i49hcSS5Tg7BYXcePdDxfYZuzbrzB1/Ehuf/BJmrZu41HS2Gax1eCggkMopJZNpVPnLmTt28fTA57wOk7UemvYUGbNnMnI98dStlw5nuzXl8f6PMxrQ4Z5HS0qxMXF8ey/BnJS3XpkZGTweN9HeOKxR3n5lde9jhZV9DoOj/ZXdOCJAc94HSNqpKSkcnXHzmRlZfHCs/0LrMvKyqJH966cfMqpjB4/mdSyZVnz6y+ULp3kTdgIpnEOn8njR1OyZKkCy6ZOHMs3n0/hyUFvULXGCcz931f8++k+1Kxdl+q1ansTNALsyfHx1f/9TmJ8HP84s1qBdUmJ8cxa/TsrfttNVm4eLeqU574Wteg/bTU79uYCcMOZ1aiWWpKXv13LloxsypZKICEuxo7Q/oLlP83ntef6cst9fTntvBbgHGnrfi2wzS8rlrB4/veUrVDJo5QSi3RKRQg0a/432rRtT/UaNb2OEtXGj/2QW7veTo2aNUlJSeGBB3vz3bffkJa20etoUeG+nr1o2KgxiYmJVKhQgS7/uIn5c+d4HSvq6HUskei8Zi245PJ2VKteo8i6zyZ9QmZmBg/2eZxy5csTFxfHiSfVpUxysgdJI5vGOTzSNqxl+sSx3HhnjwLLN29cT+NTz6JazdqYGec2b0VKalnWr1ntUdLIsHTLbuauT2fb7uwi6+as38WitAz25uSR5+DrX3aQlZtH7fKlAaiSXIIWdcrzzryNbMnw33/Xvly278kJ6z5EovEjXqdVm6s5u8WFJCaWILFESU6o2/DA+pycbN75zz+58Z4+JCToM2cvWRi/ioOwFRzMrISZ3WRmFwdudzGzV8zsHjNLDFcOiQ7p6els2pRG48ZNDiyrWasWycnJrFy+3MNk0WvO7O+p36Dh4TeUI6bXcfjM/Hw6rVucx9VXXMbgFweyZ7c9kbMAACAASURBVM9uryNFrYXz5lCjZi2e7f8YbS9sRpdr2vPBqBFex4o6GufgyMvL4/UXnuLGO3uSlJxSYN3Fba9m/Zr/Y8PaX8jz+Zj99ef4fD4anXKmR2mjT7XUkiSXSGBjehYADY4rw94cH2fXKMu/2tXnubb16HJGVUom6DPSP5O1by+/rlqKz+djQI+b6NHlMgb2uYs1q5Yd2GbiqGE0PPUs6jY6xcOkEovC+a/3baAd0MPM3gM6Aj8A5wDqHZajsme3/2AhOaXgJzkpKalk7tY5fsH2+YxpjPtwDL379PU6SlTR6zg8Onf5B+MnTuGLr79n0L9fYcH8uTzT/3GvY0WtnTt3sGDeHBqdfAqfTPuSJ575F+8OH8r0KZO8jhZVNM7BMeWj9ylXoSLntmhdZN1xVavT8JQzePD26+jSphmvDuxPt559Kas5doIipWQ83ZvWZMbKbWzN9HczJJeIp3RiPMenlKT/tNU8N/NXapYrRcdTj/c4bfG2OzMDl5fHnK9mcFvPx3lxxCROPvM8BvfvxZ7MDNasWsa872ZyzU3dvY4qEHMtDuEsOJzinLsOuBq4FPi7c+494FbgjEPdycy6mdk8M5s3fNjQMEWV4i6pTBkAMjMKHpRlZKSTXEbtpME0Y9pUnn7yCQa/8hqNGp/sdZyootdxeDRq3ISKFSsRFxfHSXXr0av3o3z++XSys4u2+8qxS0oqQ+XjqtCpy40kJpagYeMmXNq2Pd98NdPraFFF43zsNm9cz6Rxo+h638MHXT/sP/9izeoVvDJyIqOnfk+/51/lzZef48d5s8OcNPqULZVArwtqs3RLJhMWbz2wfF9uHgATl2xlX24e6ftymbpiG6dVSznUQwlQKjB3S/NL2lGzTj0SEhNp2/FmfLm5rFyykLcGP8MN3R86sJ1IOIXzBJ44MysBlAGSgLLA70BJ4JCnVDjnhgJDAfbm4MKQUyJAamoqVatWY9myJTRs1AiADevXk5mZSb0GDTxOFz0+mTCel14YyMuvvM7pZ6qFNNj0OvZGXGDyMef0JyUU6jVoyIplS4ost1ibljvENM7HbvniRaTv2sGDt18HQF7gd8JD3a6n8y138euqZVx2ZScqV6kKQIOTT6Nhk9NZOOc7Tjv7fM9yR7qKSYk8cEFtFqalM/6nLQXWrd+5DwCnt/xHJalMMpWqVMUKf6Rtxo7tv5G27hfefPHJA4t3Z2bw3msv8PO87+nW+6kwp5VYE84Oh+HAcmAR8Bgw1szeBOYCY8KYI+R8Ph9ZWVnk5PgnuMnKyiIrK0tvboPs2o6deHv4m2zY4D9AG/zSCzRr3oLqB5lcS47e6JHv8u9BA3ltyDAVG0JIr+PQm/bZZDLS0wFYt3YN/x70PC1btqZkyZIeJ4tc+//O5R7k71zbKzqwa+dOxn84Gp/Px6qVy5nx2WRaXqhLCR4tjXNoNW15Cf9992MGDhnNwCGjefTZlwHo969XaHlpOxqcfBrffPEZv2/zfwK/atlilv64gBPraT6jP2NAQpwRHyjuJsTZgatMVEkpQe9WdZi7fleRYgPA6m172LBzH1c2Po4S8UZKyXgurV+JhRvTw7kLEal122v57vNJpK37FZ8vl6njR5KYmMh5LS9j4Nuf8OR/3jvwVa5CJa69qTtd7nzQ69gxycL4X3Fg4TwINrNqAM65NDMrB1wMrHPOHdHU95HS4fDJxx/xZL9HiyyfPO2LYn8QEUkfjPh8Pga/NIiJH39EdnY25zdrzhP9n6J8MT+3Mi9CCk9nNGlIQkICiYklCiz/39wFHiU6OnER8mKO1NcxQK4vMl7L3W67kVUrV5KdnU2FChVofdHFdLvrPpIjYDb/vTk+ryMc1JSJE/jngH5Flo/9dDpVq1Vnwbw5/Pel51m/di2VKlemY5cbubZTFw+SRrZoGue0HXu9jnBYWzence8/ruT19ydTsXIV9uzOZOSb/2H+99+wd89uypavQOvLr+SaLrd5HfWgXvthndcRAGh6QjluOad6keV9p6ykfePKNKtdnn25BX+3jZq/iTnrdwFQISmRLmdUpV7lJPbm5LFwQzoTFm8huxj8zbnxtGqH38gjzjk+GfUmX039mJycbGqdWJ/Od/Sk1on1i2z78G0duPrGO2nauo0HSQ+vRb3ykfEm7i9atWVv2F7M9aqU9nwsw1pwOFaRUnCIZBFyjBbRIqXgEOkipeAQySKl4BDJimvBQeRoRULBIdIVl4JDNCvOBYdoEu0Fh9Vbw1dwqHuc9wUHXWNGRERERERERIIunJNGioiIiIiIiMQsz1sOwkwdDiIiIiIiIiISdOpwEBEREREREQmHGGtxUIeDiIiIiIiIiASdOhxEREREREREwsBirMVBHQ4iIiIiIiIiEnTqcBAREREREREJA4utBgd1OIiIiIiIiIhI8KnDQURERERERCQMYqzBQR0OIiIiIiIiIhJ86nAQERERERERCYcYa3FQh4OIiIiIiIiIBJ0KDiIiIiIiIiISdDqlQkRERERERCQMLMbOqVCHg4iIiIiIiIgEnTocRERERERERMLAYqvBQR0OIiIiIiIiIhJ86nAQERERERERCYMYa3BQh4OIiIiIiIiIBJ86HERERERERETCQHM4iIiIiIiIiIgcI3POeZ3hiO3NIXLCRqhYq7iJyF/ny9OvZIl82bl5XkeICRrn0NuanuV1hKjX6rFPvY4QE7aPuD6qj0g27MgO2xuoGuVLeD6W6nAQERERERERkaDTHA4iIiIiIiIiYRBrHeXqcBARERERERGRoFOHg4iIiIiIiEgYxFiDgzocRERERERERCT41OEgIiIiIiIiEgaaw0FERERERERE5Bip4CAiIiIiIiIiQadTKkRERERERETCwGJs2kh1OIiIiIiIiIhI0KnDQURERERERCQcYqvBQR0OIiIiIiIiIhJ86nAQERERERERCYMYa3BQh4OIiIiIiIiIBJ86HERERERERETCwGKsxUEdDiIiIiIiIiISdOpwEBEREREREQkDi7FZHNThICIiIiIiIiJBpw4HERERERERkXCIrQYHdTiIiIiIiIiISPCpw0FEREREREQkDGKswUEFh1CYOmUyH4wZxcoVy9m3bx/zf1zqdaSo5PP5ePnfg5j48QSysrJo2qwFj/cfQPnyFbyOFjU0xqGnMQ6fvLw8brupCz/9uIjPZnxJleOP9zpSVNI4B8+MqVMY9+FoVq1cQda+fXw37+cD6/73zVeMeu8dVq9aQZ4vjxPr1uWue3ty+plne5g48nwxfQoTxo5h9Sr/GM+a/WOB9Z+M/4APRr/L9t+2UqPmCdzb62HOOOtcj9JGtry8PPr16MrKpT8xZMwUKlauAsDmtPW8+8ZgFi+aC0D1WnV4evAwEhISvYxbrD3Z6TQuPb061SsksXtfDtN/TGPAhz+yc3f2gW2ua16b3h2aUKVsaZZt2Envd+fx45odAJRKjOe1bufTpFZ56hyXzL8m/MyLE5d4tTsS5XRKRQiklk2lU+cu9H6kr9dRotpbw4Yya+ZMRr4/lukzvwbgsT4Pe5wqumiMQ09jHD6j3nuHUqVKex0j6mmcgyclNZVrO17PAw/1KbIuPSOdjp1vYNzEqXw281suvbw9D9x7J1s2b/IgaeRKSSlLh7935r5ejxRZN+vzaQx74xUG/PNFpsyazZXXdOSRnvdojP+iSeNGUbJUqQLLdu3cweM9b+eEk+rz+ujJvD1hFl3ve4S4uHiPUkYGX56j+xvfU/ee8Vzw+FSqVUjilTvOO7D+vHqVeOHmc3hoxDxOuns8n87bwJherUgp5f+s2eGYs3obvd6ew4Jftnu1GzHLLHxfxYEKDiHQrPnfaNO2PdVr1PQ6SlQbP/ZDbu16OzVq1iQlJYUHHuzNd99+Q1raRq+jRQ2NcehpjMNj7ZpfGTvmfR54SMWcUNI4B9f5zVpwaZt2VDvI+4nL215BqwsvJiUllYSEBK7t1JnSSUksXbLYg6SR69ymzbn4srZUq16jyLovv5jOpW3aU69BQ+Lj47nq2usoV6ECn336sQdJI1va+rVMmziWm+7sWWD5pHEjqXTc8Vx3852USU4hPj6eug0aExenQ5Q/88y4n/h53Q5yfY7tGVkMmb6SFg2rHFh/U6u6TJ63ni8XbyY7N4//TllGdq6Pdmf5f5dk5eTxxrQVfLt8K/tyfF7thsSIsP5rNrMTzewhM3vZzF4ys+5mlhrODBId0tPT2bQpjcaNmxxYVrNWLZKTk1m5fLmHyaKHxjj0NMbhkZeXx4AnHqPnQw+TkpLidZyopXH21upVK9m1cycn1a3ndZSo4ZzDOVd4IatW6vfz0cjLy+O1QQO4qXtPyiQX/N2weNE8Klauwj/73s8tHVrT6/br+PrzKR4ljVwXNK7C4nU7Dtw+uWY5Fq3ZUWCbn9fu4ORa5cIdTSR8BQczux94AygFnAOUBGoCs82sVbhySHTYs3s3AMkpyQWWp6Skkrk704tIUUdjHHoa4/AYPfJdKlaqxIUXXeJ1lKimcfbO779v59GHetDlxlupdUJtr+NEjaYtWjLjs0ksX7qY3Nwcxn84mi2bNx343S1HZvJH71OufCXOa3FhkXUZu3Yy59tZtL7sSoaPn8HN3R/g9UFPs+znhR4kjUxXnF2DW1vXpe+oBQeWJZdOIGNvdoHtdu3JIaW05sUoDiyM/xUH4Zw08g7gdOecz8xeAqY451qZ2RDgE+CMMGaRCJdUpgwAmRkFD8oyMtJJLpN8sLvIUdIYh57GOPTWrVvLyBFvM/KDcV5HiWoaZ+/8tnUr99/VlfOaNufu+x/wOk5Uubzdlfy+fRtPP96HXbt20KLlhZx17vmkppb1OlrE2LRxPZ+OHcnzr7930PWlkspQv/EpNG15MQCnnX0+p5/TlHn/+5pGp+jQ4HCuPKcmL91yDjcM/pqf1v7R0ZC5N5eU0iUKbFs2KZFft+rDDAm/cF+lIgHw4e9uSAZwzq0zs0OW28ysG9AN4L+vDaHr7d3CkVOKudTUVKpWrcayZUto2KgRABvWryczM5N6DRp4nC46aIxDT2MceosWzGfHjt/pdPUVAOTl+dujr7v2Ku6+rwedOnfxMl7U0Dh7Iy1tI/fdeRstW1/E/b00b0awmRk33NyVG27uCkBOTg7XXXUZN3e90+NkkWP5zwtJ37WDXl07ARw4ReXBOzrT+da7qHNSfTZtXF/0jsVltrtirMvf6vBU5zPoMvhr5qzaVmDdkvU7Oa12+QLLmtQqz6R5G8IZUQ4h1l7e4Sw4DAPmmtkPwN+A5wHMrDLw+6Hu5JwbCgwF2JuDO9R2xYnP5yM3N5ecnBwAsrKyAChRogQWa6+wELq2YyfeHv4m55x7HuXKlWfwSy/QrHkLqh9k4if5azTGoacxDq1LLmvDeec3O3B7y5bN3PKPzrw2dBi165zoYbLoonEOjf3vJ3IP8n5i7Zpfua97V9pd2YHu9/TwMmZE+7P3bLt3Z7Ltt62cUPtEdu3cwRuv/Jsyyclc3u4qLyNHlGatLuHUs/64esL237bS975b6Pf8q1SvVZsT6zXi8Z5dmfPtLM5u1pKlP87nx/mz6dD5Fu9CR4Bul9Snd4cmdBz0JQt/LXoY9e6Xq/nwoVZc0LgK36/4jW6X1qdkYjyT5/9R3CmREIcZxMUZ8XFGycQ4fHmOXF9EHG5JBLEik+GE8snMTgYaAYudc0c9406kFBw++fgjnuz3aJHlk6d9UewPIiKpHuLz+Rj80iAmfvwR2dnZnN+sOU/0f4ry5St4HS1qaIxDL5LH2JcXEb+SC0jbuIH2l1/MZzO+pMrxx3sdJ2pF0jhn5+Z5HeGQJk2cwDNPPlZk+UeTZzB8yKtMnvgxpUsXvATpI/36c3nbK8IV8YgV13H+7NOPee6pfkWWf/DJNOLi4ni4x11s3rSRhMREmja/gLt7PESFipU8SHp4W9OzvI5wWFs3p3H3DVcwZMwUKlb2X1Xhf1/NYMxbr7N92xaOO746HW+6g2Yti+dcMK0e+9TrCABsH3E9Obl5ZOUWvMLECXf+cVrbdc1r83CHU6hSrhTLNuzioRFz+THfRJILB11BrcoFT998/5tfuHfYD6ENfwS2j7g+go5Ijt6OPeGr6pRPivd8LMNacDhWkVJwiGSRVHAQEW9FYsFBpLDieiAcbTTOoRcJBYdIV1wKDtFOBYfgKQ4Fh3DP4SAiIiIiIiISk2LtA96wXRZTRERERERERGKHOhxEREREREREwsCIrRYHdTiIiIiIiIiISNCpw0FEREREREQkDDSHg4iIiIiIiIjIMVKHg4iIiIiIiEgYxFiDgzocRERERERERCT41OEgIiIiIiIiEg4x1uKgDgcRERERERERCToVHEREREREREQk6HRKhYiIiIiIiEgYWIydU6EOBxEREREREREJOnU4iIiIiIiIiISBxVaDgzocRERERERERCT41OEgIiIiIiIiEgYx1uCgDgcRERERERERCT51OIiIiIiIiIiEQ4y1OKjDQURERERERESCTgUHERERERERkTCwMP53RHnMLjezFWa22sz6BHt/VXAQERERERERiTFmFg+8CrQBGgPXm1njYD6H5nAQERERERERCQMrXnM4nAusds79AmBmY4CrgKXBegJ1OIiIiIiIiIjEnurA+ny3NwSWBU1EdTiUToy8OT3NrJtzbqjXOaKZxjj0NMbhEXnjHHG/kiNwjCNPpI1xmRLxXkf4SyJtnCHyxjnSxrhKaqLXEY5apI3x9hHXex3hqEXaGMeCUgnhewNlZt2AbvkWDQ3360EdDqHX7fCbyDHSGIeexjg8NM6hpzEOPY1xeGicQ09jHHoa49DTGMcw59xQ59zZ+b4KFxs2AjXz3a4RWBY0KjiIiIiIiIiIxJ65QD0zq2NmJYDOwMRgPkFEnVIhIiIiIiIiIsfOOZdrZvcC0/Cf+/aWc25JMJ9DBYfQ0zlToacxDj2NcXhonENPYxx6GuPw0DiHnsY49DTGoacxlj/lnJsCTAnV45tzLlSPLSIiIiIiIiIxSnM4iIiIiIiIiEjQqeAQImZ2uZmtMLPVZtbH6zzRyMzeMrOtZrbY6yzRysxqmtksM1tqZkvMrIfXmaKNmZUyszlm9mNgjAd4nSlamVm8mS00s0leZ4lWZrbGzH42s0VmNs/rPNHIzMqZ2TgzW25my8ysqdeZoomZNQi8fvd/pZtZT69zRSMzeyDwd2+xmb1vZqW8zhRtzKxHYHyX6HUsXtEpFSFgZvHASuASYAP+2T+vd84t9TRYlDGzC4BM4F3nXBOv80QjM6sKVHXOLTCzFGA+0EGv5eAxMwPKOOcyzSwR+Bbo4Zyb7XG0qGNmvYCzgVTnXHuv80QjM1sDnO2c2+Z1lmhlZiOAb5xzwwIziic553Z6nSsaBd7PbQTOc86t9TpPNDGz6vj/3jV2zu01sw+BKc65d7xNFj3MrAkwBjgXyAamAt2dc6s9DSYxRx0OoXEusNo594tzLhv/P/arPM4UdZxzXwO/e50jmjnnNjnnFgR+zgCWAdW9TRVdnF9m4GZi4EuV4CAzsxpAO2CY11lE/iozKwtcAAwHcM5lq9gQUhcB/6diQ8gkAKXNLAFIAtI8zhNtGgE/OOf2OOdyga+AazzOJDFIBYfQqA6sz3d7AzpIkwhnZrWBM4AfvE0SfQKt/ouArcAM55zGOPgGAw8DeV4HiXIOmG5m882sm9dholAd4Dfg7cDpQcPMrIzXoaJYZ+B9r0NEI+fcRmAQsA7YBOxyzk33NlXUWQz8zcwqmlkS0Bao6XEmiUEqOIjIYZlZMjAe6OmcS/c6T7Rxzvmcc6cDNYBzA22QEiRm1h7Y6pyb73WWGNDCOXcm0Aa4J3DqmwRPAnAm8Lpz7gxgN6B5okIgcLrKlcBYr7NEIzMrj7/7tw5QDShjZv/wNlV0cc4tA54HpuM/nWIR4PM0lMQkFRxCYyMFK4g1AstEIk5gXoHxwCjn3Ede54lmgdboWcDlXmeJMs2BKwPzC4wBLjSzkd5Gik6BTy1xzm0FJuA/xVCCZwOwIV8X1Dj8BQgJvjbAAufcFq+DRKmLgV+dc78553KAj4BmHmeKOs654c65s5xzFwA78M8xJxJWKjiExlygnpnVCVTIOwMTPc4kctQCExoOB5Y5517yOk80MrPKZlYu8HNp/JPNLvc2VXRxzj3qnKvhnKuN//fxTOecPkkLMjMrE5hclkCb/6X4W3olSJxzm4H1ZtYgsOgiQJP4hsb16HSKUFoHnG9mSYH3GhfhnydKgsjMjgt8r4V//obR3iaSWJTgdYBo5JzLNbN7gWlAPPCWc26Jx7Gijpm9D7QCKpnZBuBJ59xwb1NFnebAjcDPgTkGAPo656Z4mCnaVAVGBGZDjwM+dM7pso0SiaoAE/zHDiQAo51zU72NFJXuA0YFPtD4BbjV4zxRJ1AwuwS40+ss0co594OZjQMWALnAQmCot6mi0ngzqwjkAPdoklnxgi6LKSIiIiIiIiJBp1MqRERERERERCToVHAQERERERERkaBTwUFEREREREREgk4FBxEREREREREJOhUcRERERERERCToVHAQEZGIYWb9zczl+0ozs/FmdlIIn7N94LlqB27XDtxufxSP0cnMbglipuRAhj99zMA29x7jc/U3s23H8hj5HusdM5sXjMcSERGR4i/B6wAiIiJHaRdweeDnE4GngS/M7GTn3O4wPP8moCmw/Cju0wmoBLwTikAiIiIixZEKDiIiEmlynXOzAz/PNrN1wDdAW2Bs4Y3NrLRzbm+wntw5lwXMPuyGIiIiIjFOp1SIiEikmx/4XhvAzNaY2Ytm9riZbQDSA8vjzKyPma02sywzW2lmN+d/IPPrb2ZbzSzDzN4FUgttc9BTKszsDjP72cz2mdkWMxtnZmXN7B3gWqBlvlNB+ue731VmNi9wv81mNtDMEgs99rWBvHvN7GugYRDGDTNrZ2YzAvubbmazzezSQ2zb3MwWBHIuMrMWB9nmdjNbEhjftWb28GGev5yZDQucGrPPzNaZ2ZvB2DcRERHxnjocREQk0tUOfN+cb1kXYAlwN3/8rfsvcDPwFLAAuAR4y8y2O+cmBba5H3gC+Cf+rolrgIGHC2Bm/QKP+xrQG0gC2gHJ+E/5qAWUC+QB2BC4XyfgfWAI0Bc4CXgO/wcCDwW2ORP4AJgA9ACaAB8eLtMRqgN8CgwC8oA2wGdmdoFz7rt82yUBIwPZNgEPBrar55zbHMjZG/+4DQS+BM4CnjazPc65Vw7x/C8BzYAH8P//qwlcEKR9ExEREY+p4CAiIhHHzPb//ToR/0F+BvB5oc3aO+f2BbavC9wF3OqcGxFY/7mZVQWeBCaZWTzwCDDEOdcvsM00M5sBVP+TLOXwFwsGO+d65Vv1Ub5tfgfi8p0KgpkZ8ALwrnPu7nzLs4BXzew559x2oA+wEujknHP4D/RLAM/8+SgdXv5CgJnFAbOAk4GuQP6CQ2ngMefc6MC2s4B1QE+gj5ml4h/HZ5xzAwL3mWFmSUA/M3vdOec7SIRzgVedcx/kWzbyWPdLREREigedUiEiIpGmIpAT+FqBv+hwnXNuU75tvthfbAi4CP8n+BPMLGH/F/AFcHqg2FATqAp8Uuj5PuLPNcV/QP72Ue5HffydDx8WyjQTKIW/kwH8B+UTA8WGI810RMyshpmNMLONQC7+Mb00kK2wCft/cM5lAjMC2cA/BmWAsQfZlypAjUNEWAT0NrO7zexgzykiIiIRTB0OIiISaXYBFwMOfxt+WqGDcYAthW5XAuID9z2YqsDxgZ+3FlpX+HZhFQPfN/3pVkVVCnyfcoj1NQPfj/8LmQ4r0NEwEUjBfxrJamA3/lNDjiu0eeZBJt7cCpwa+Hn/viw5xNPVBNYeZPm9ged7An9Xx2rgcefcmKPYFRERESmmVHAQEZFIk+ucm3eYbQoXIH7H/wl+c/ydDoVt5Y+/iYUPtgvfLmx74HtVYNthti2cCaAbsPAg638NfN/8FzIdibrAGUAb59zU/QvNrPRBtk0+yNU+juOPIsv+fWlP0WIP+DtRinDO7cQ/b8b9ZnYq8DAwysx+cs4tPaq9ERERkWJHp1SIiEgsmIm/w6Gsc27eQb6ygfX4D+6vKnTfaw7z2N8De/FPSHko2fhPk8hvBbARqH2ITPsLGXOBKwNzPhxppiOxv7CQtX+BmZ2AvyhzMFfn2y4Z/6SbcwKL9o9BtUPsS8bhwjjnfsI/4WYcQboKh4iIiHhLHQ4iIhL1nHMrzOwNYIyZDQTm4S8AnAzUd87d7pzzBdYNMrNt+K9ScS3Q6DCPvdPMngaeDUzmOAUoif8qFQOccxuB5cBVZtYB/xUq0pxzaWb2IPBeYNLFz/AXJk4EOgB/d87tAZ4HfsA/18Nw/HM7dD2K3T/dzP5eaNlvwOxAlhfN7HH8p1YMwF8EKWxvYP+SgTT8V9AoAbycbwz6Ay8HihZf4y8c1AdaO+euPshjYmbf4p8bYjH+rpQ78J/WMedg24uIiEhkUcFBRERixT34r/ZwB/55A9KBpcDwfNsMBioA3fFfgWEigTb/P3tg59xzgStR9ADuBHbgP+je/8n+a/hPX3gLKI//wL6/c+4DM0vHf5WL2wAf8AswCX/xAefcPDPrjP+SlB/jL5Zcx5EflHelaIHiK+dcKzO7BngVGIe/+PAs0Io/Jqzcbw9wE/5LizbCX0Bpm3+iTufcQDNLw3+JyweBffjH+wMO7XvgFvyXNvXhP7WkjXNuwxHum4iIiBRjVnSeLRERERERERGRY6M5HEREREREREQk6FRwEBEREREREZGgU8FBRERERERERIJOBQcRERERERERCToVHEREREREREQk6FRwEBEREREREZGgU8FBRERERERERIJOBQcRERERERERCToVHEREaIMwVgAAAA1JREFUREREREQk6P4f+/tp4AKAZRMAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZlT_NllShnuM",
        "colab_type": "text"
      },
      "source": [
        "## Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "83ffeUfboOen",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "0bb73042-c1b2-4fbe-8242-07776288edc1"
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X_rem, y_rem, test_size=0.15, random_state=42)\n",
        "\n",
        "models = LinearRegression()\n",
        "cv = cross_validate(models,X_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_test,y_test)))\n",
        "print(\"CV Scores: {}\".format(cv['test_score']))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean training accuracy: 0.6561193271037121\n",
            "Test accuracy: 0.6725718445462191\n",
            "CV Scores: [0.66099181 0.65608622 0.65127996]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lKg48RAjm7B-",
        "colab_type": "text"
      },
      "source": [
        "### Log Transformation Experiment"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rreqBQe8hmd6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "90e7b082-f512-4b7e-fe29-ed02c4d33c14"
      },
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "\n",
        "Xreg = X_rem.copy()\n",
        "for col in ['total_bedrooms','total_rooms','population','median_income','households']:\n",
        "  Xreg[col] = log_transform(Xreg[col])\n",
        "\n",
        "y_reg = log_transform(y_rem)\n",
        "X_train, X_test, y_train, y_test = train_test_split(Xreg, y_reg, test_size=0.15, random_state=42)\n",
        "\n",
        "models = LinearRegression()\n",
        "cv = cross_validate(models,X_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_test,y_test)))\n",
        "print(\"CV Scores: {}\".format(cv['test_score']))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean training accuracy: 0.6991305415185257\n",
            "Test accuracy: 0.7145446982807462\n",
            "CV Scores: [0.70058077 0.70453321 0.69227765]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MruXuY37o8op",
        "colab_type": "text"
      },
      "source": [
        "### New Feature Generation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FcYO-Jfr3OKW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.metrics import silhouette_score\n",
        "from sklearn.cluster import KMeans"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UjLlNhKXopVZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "outputId": "c9fdf306-0c40-4176-a948-a3c3ab3189f1"
      },
      "source": [
        "cls = X_rem.iloc[:,0:2]\n",
        "for i in range(2,20):\n",
        "  cluster = KMeans(n_clusters=i,random_state=42)\n",
        "  cluster.fit(cls)\n",
        "  label=cluster.predict(cls)\n",
        "  print('Silhouette Score(n={}): {}'.format(i,silhouette_score(cls, label)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Silhouette Score(n=2): 0.7584148710130193\n",
            "Silhouette Score(n=3): 0.6601931476905184\n",
            "Silhouette Score(n=4): 0.6160995190976558\n",
            "Silhouette Score(n=5): 0.5713551277050426\n",
            "Silhouette Score(n=6): 0.5739120886936904\n",
            "Silhouette Score(n=7): 0.5779067913147109\n",
            "Silhouette Score(n=8): 0.5204593591731302\n",
            "Silhouette Score(n=9): 0.46374298051632606\n",
            "Silhouette Score(n=10): 0.4614078597868947\n",
            "Silhouette Score(n=11): 0.4747993138646691\n",
            "Silhouette Score(n=12): 0.4827013494498321\n",
            "Silhouette Score(n=13): 0.46506446229570025\n",
            "Silhouette Score(n=14): 0.4727295394212954\n",
            "Silhouette Score(n=15): 0.4784110078988257\n",
            "Silhouette Score(n=16): 0.4889067007660901\n",
            "Silhouette Score(n=17): 0.49431992451575646\n",
            "Silhouette Score(n=18): 0.4619317540444434\n",
            "Silhouette Score(n=19): 0.45502676299830025\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cVp6g6v7pcTt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 895
        },
        "outputId": "4f4548fa-ccaf-47d0-b2d8-b118046d2dd5"
      },
      "source": [
        "cluster = KMeans(n_clusters=3,random_state=42)\n",
        "cluster.fit(cls)\n",
        "label=cluster.predict(cls)\n",
        "cls['clusters'] = label\n",
        "plt.figure(figsize=(20, 15))\n",
        "sns.scatterplot(cls.latitude, cls.longitude,hue =cls.clusters )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f469c1651d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "blGU7m5wplr_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "41434c41-1b8b-434a-f60d-87117d3d2619"
      },
      "source": [
        "X_exp = Xreg.copy()\n",
        "X_exp['geocluster'] = label\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X_exp, y_reg, test_size=0.15, random_state=42)\n",
        "\n",
        "models = LinearRegression()\n",
        "cv = cross_validate(models,X_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_test,y_test)))\n",
        "print(\"CV Scores: {}\".format(cv['test_score']))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean training accuracy: 0.7183396386358564\n",
            "Test accuracy: 0.7294160703097251\n",
            "CV Scores: [0.71892363 0.72151491 0.71458038]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5ku_oWfCtow2",
        "colab_type": "text"
      },
      "source": [
        "We see that log tranformation and geographic feature generation increased the linear regression model R-squared values. Thus, for model selection, I will use `X_exp` as main feature dataset. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "05-xpLoPn1Po",
        "colab_type": "text"
      },
      "source": [
        "# Model Selection  \n",
        "\n",
        "## Linear Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WyDTa_fwv7Vj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "73283c42-094c-4ffc-8b5b-1487e779f87d"
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X_exp, y_reg, test_size=0.15, random_state=42)\n",
        "\n",
        "models = LinearRegression()\n",
        "cv = cross_validate(models,X_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_test,y_test)))\n",
        "print(\"CV Scores: {}\".format(cv['test_score']))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mean training accuracy: 0.7183396386358564\n",
            "Test accuracy: 0.7294160703097251\n",
            "CV Scores: [0.71892363 0.72151491 0.71458038]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t5nREDjBwC3s",
        "colab_type": "text"
      },
      "source": [
        "## Lasso Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rIl6ar7qv8JV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "outputId": "826d7ffb-8713-4fd8-f26f-95f714ad5111"
      },
      "source": [
        "from sklearn.linear_model import Ridge, Lasso\n",
        "from sklearn.model_selection import RandomizedSearchCV, GridSearchCV\n",
        "from time import time\n",
        "params_lasso = {'alpha': [0,0.01,0.001,0.0001,0.00001]}\n",
        "\n",
        "las = Lasso(random_state = 42)\n",
        "regressor_l = GridSearchCV(las, params_lasso, cv = 3,n_jobs=-1)\n",
        "\n",
        "regressor_l.fit(X_train,y_train)\n",
        "print(\"Tuned Lasso Regression Parameters: {}\".format(regressor_l.best_params_)) \n",
        "print(\"Mean of the cv scores is {:.6f}\".format(regressor_l.best_score_))\n",
        "print(\"Test Score {:.6f}\".format(regressor_l.score(X_test,y_test)))\n",
        "print(\"Seconds used for refitting the best model on the train dataset: {:.6f}\".format(regressor_l.refit_time_))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tuned Lasso Regression Parameters: {'alpha': 0.0001}\n",
            "Mean of the cv scores is 0.699141\n",
            "Test Score 0.714341\n",
            "Seconds used for refitting the best model on the train dataset: 0.095658\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V3Hh3hHPx5Uq",
        "colab_type": "text"
      },
      "source": [
        "## Ridge Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J7IQP2Nzx8Co",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "outputId": "e8266202-7000-466a-f73c-beec2a162048"
      },
      "source": [
        "from sklearn.linear_model import Ridge, Lasso\n",
        "from sklearn.model_selection import RandomizedSearchCV, GridSearchCV\n",
        "\n",
        "params_ridge = {'alpha': [0,0.01,0.001,0.0001,0.00001]}\n",
        "\n",
        "rid = Lasso(random_state = 42)\n",
        "\n",
        "regressor_r = GridSearchCV(rid, params_ridge, cv = 3,n_jobs=-1)\n",
        "\n",
        "regressor_r.fit(X_train,y_train)\n",
        "print(\"Tuned Support Vector Classification Parameters: {}\".format(regressor_r.best_params_)) \n",
        "print(\"Mean of the cv scores is {:.6f}\".format(regressor_r.best_score_))\n",
        "print(\"Test Score {:.6f}\".format(regressor_r.score(X_test,y_test)))\n",
        "print(\"Seconds used for refitting the best model on the train dataset: {:.6f}\".format(regressor_r.refit_time_))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tuned Support Vector Classification Parameters: {'alpha': 1e-05}\n",
            "Mean of the cv scores is 0.718344\n",
            "Test Score 0.729280\n",
            "Seconds used for refitting the best model on the train dataset: 0.321649\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "48kU69sLySTD",
        "colab_type": "text"
      },
      "source": [
        "## LightGBM"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D6pKEOXbyFsB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "outputId": "b1d7a300-693c-403b-f1a6-b6788449d2b1"
      },
      "source": [
        "from sklearn.metrics import r2_score\n",
        "import lightgbm as lgb\n",
        "params = {}\n",
        "params['learning_rate'] = 0.01\n",
        "params['boosting_type'] = 'gbdt'\n",
        "params['objective'] = 'regression'\n",
        "params['num_leaves'] = 10\n",
        "params['max_depth'] = 100\n",
        "params['reg_alpha'] = 0.001\n",
        "params['min_child_samples'] = 20\n",
        "params['n_estimators'] = 10000\n",
        "params['random_state'] = 42\n",
        "\n",
        "models = lgb.LGBMRegressor(\n",
        "    objective = params['objective'],\n",
        "    n_estimators= params['n_estimators'],\n",
        "    random_state = params['random_state'],\n",
        "    boosting_type = params['boosting_type'],\n",
        "    num_leaves = params['num_leaves'],\n",
        "    reg_alpha = params['reg_alpha'],\n",
        "    min_child_samples = params['min_child_samples'],\n",
        "    learning_rate = params['learning_rate'],\n",
        "    max_depth = params['max_depth'],\n",
        "\n",
        ")\n",
        "\n",
        "selector = SelectFromModel(models).fit(X_train, y_train)\n",
        "\n",
        "X_lgb_train = selector.transform(X_train)\n",
        "X_lgb_test = selector.transform(X_test)\n",
        "\n",
        "lgb_features = X_train.loc[:,selector.get_support()].columns.tolist()\n",
        "print(\"Selected Columns:\",lgb_features,\"\\n\")\n",
        "\n",
        "s = time()\n",
        "cv = cross_validate(models,X_lgb_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "f = time()\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_lgb_test,y_test)))\n",
        "print(\"CV Scores: {}\".format(cv['test_score']))\n",
        "print(\"Test Adjusted R-squared Value:\",1 - (1-cv[\"estimator\"][0].score(X_lgb_test,y_test))*(len(y_test)-1)/(len(y_test)-X_lgb_test.shape[1]-1))\n",
        "print(\"Passed time:\",f-s)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Selected Columns: ['longitude', 'latitude', 'housing_median_age', 'total_rooms', 'population', 'median_income'] \n",
            "\n",
            "Mean training accuracy: 0.8499798793046267\n",
            "Test accuracy: 0.8496586780110569\n",
            "CV Scores: [0.84505666 0.8566446  0.84823837]\n",
            "Test Adjusted R-squared Value: 0.8493308989660229\n",
            "Passed time: 27.554120779037476\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-LMsPp341MLI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "f1eddb3c-125d-45fe-d26d-4e689ae31150"
      },
      "source": [
        "fi_dt = pd.DataFrame({'Feature':lgb_features,\n",
        "       'Importance':cv[\"estimator\"][0].feature_importances_}).sort_values(by = \"Importance\",ascending = True).reset_index(drop = True)\n",
        "       \n",
        "fig = px.bar(fi_dt, x='Importance', y='Feature',orientation='h',color='Importance')\n",
        "fig.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
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              "            Plotly.purge(gd);\n",
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              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
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              "</body>\n",
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          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YCxH3wsOtZJx",
        "colab_type": "text"
      },
      "source": [
        "## Random Forest Regressor"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q0RqJfGRz_Sa",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "outputId": "087ec660-c310-4f3d-dfd2-228949ecdefc"
      },
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "\n",
        "selector = SelectFromModel(RandomForestRegressor(random_state = 42)).fit(X_train, y_train)\n",
        "\n",
        "X_rnd_train = selector.transform(X_train)\n",
        "X_rnd_test = selector.transform(X_test)\n",
        "\n",
        "rnd_features = X_train.loc[:,selector.get_support()].columns.tolist()\n",
        "print(\"Selected Columns:\",rnd_features,\"\\n\")\n",
        "\n",
        "rnd = RandomForestRegressor(random_state = 42)\n",
        "s = time()\n",
        "cv = cross_validate(rnd,X_rnd_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "f = time()\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_rnd_test,y_test)))\n",
        "print(\"Accuracy Scores of cross valdations: {}\".format(cv['test_score']))\n",
        "print(\"Test Adjusted R-squared Value:\",1 - (1-cv[\"estimator\"][0].score(X_rnd_test,y_test))*(len(y_test)-1)/(len(y_test)-X_rnd_test.shape[1]-1))\n",
        "print(\"Passed time:\",f-s)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Selected Columns: ['longitude', 'latitude', 'median_income', 'INLAND'] \n",
            "\n",
            "Mean training accuracy: 0.8320548085427665\n",
            "Test accuracy: 0.8353629037680779\n",
            "Accuracy Scores of cross valdations: [0.82754371 0.83771842 0.8309023 ]\n",
            "Test Adjusted R-squared Value: 0.8351237794453009\n",
            "Passed time: 10.22335958480835\n"
          ],
          "name": "stdout"
        }
      ]
    },
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        "id": "-F_fsF4M1P_e",
        "colab_type": "code",
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          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "fa3e88c1-03ac-4c09-abb4-0899602fec1d"
      },
      "source": [
        "fi_dt = pd.DataFrame({'Feature':rnd_features,\n",
        "       'Importance':cv[\"estimator\"][0].feature_importances_}).sort_values(by = \"Importance\",ascending = True).reset_index(drop = True)\n",
        "       \n",
        "fig = px.bar(fi_dt, x='Importance', y='Feature',orientation='h',color='Importance')\n",
        "fig.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
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              "</body>\n",
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            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pDw0yaVJ277n",
        "colab_type": "text"
      },
      "source": [
        "## XGBBoost"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FVQVwUM22Y6h",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 124
        },
        "outputId": "dadc0421-4b80-47af-c29a-83370bd9a43c"
      },
      "source": [
        "import xgboost\n",
        "\n",
        "xgb_model = xgboost.XGBRegressor(colsample_bytree=0.4,\n",
        "                 gamma=0,                 \n",
        "                 learning_rate=0.02,\n",
        "                 max_depth=100,\n",
        "                 min_child_weight=1,\n",
        "                 n_estimators=1000,                                                                    \n",
        "                 reg_alpha=0.75,\n",
        "                 reg_lambda=0.45,\n",
        "                 subsample=0.6,\n",
        "                 random_state=42)\n",
        "\n",
        "X_train_xgb = X_train.copy()\n",
        "X_train_xgb['1H OCEAN'] = X_train_xgb['<1H OCEAN']\n",
        "X_train_xgb = X_train_xgb.drop('<1H OCEAN',axis=1)\n",
        "\n",
        "X_test_xgb = X_test.copy()\n",
        "X_test_xgb['1H OCEAN'] = X_test_xgb['<1H OCEAN']\n",
        "X_test_xgb = X_test_xgb.drop('<1H OCEAN',axis=1)\n",
        "\n",
        "selector = SelectFromModel(xgb_model).fit(X_train_xgb, y_train)\n",
        "\n",
        "X_xgb_train = selector.transform(X_train_xgb)\n",
        "X_xgb_test = selector.transform(X_test_xgb)\n",
        "\n",
        "xgb_features = X_train_xgb.loc[:,selector.get_support()].columns.tolist()\n",
        "print(\"Selected Columns:\",xgb_features,\"\\n\")\n",
        "\n",
        "cv = cross_validate(xgb_model,X_xgb_train,y_train,cv = 3, n_jobs=-1, return_estimator=True)\n",
        "print(\"Mean training accuracy: {}\".format(np.mean(cv['test_score'])))\n",
        "print(\"Test accuracy: {}\".format(cv[\"estimator\"][0].score(X_xgb_test,y_test)))\n",
        "print(\"Accuracy Scores of cross valdations: {}\".format(cv['test_score']))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[08:57:54] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
            "Selected Columns: ['median_income', 'INLAND', 'geocluster', '1H OCEAN'] \n",
            "\n",
            "Mean training accuracy: 0.5496175462185179\n",
            "Test accuracy: 0.5664887853807896\n",
            "Accuracy Scores of cross valdations: [0.53966767 0.56041033 0.54877464]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bh0uKor0-yiv",
        "colab_type": "text"
      },
      "source": [
        "# Conclusion"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "javmK4bx_xTl",
        "colab_type": "text"
      },
      "source": [
        "Firstly, I tried binning our label due to binomial distribution and try to solve problem with classification methods. After many trails over the bin number, I could not obtain good accuracy. During the regression approach, I applied log transformation to skewed features and label, encode ocean_proximity feature and generate new label based on geographical information. After these preprocessings, I applied 5 different algorithms: Lasso, Ridge, LightGBM, Random Forest Regressor and XGBoost. Due to the time condition, I tried to optimize hyperparameters manually. LighGBM and Random Forest performed the best results. If we check the Adjusted R-sqaured values of these algortihms, we see that LightGBM regressor gave the best result with 0.84933. However, Random Forest is faster than LightGBM."
      ]
    }
  ]
}