UsingPycaret_Regression.ipynb

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            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hamzafarooq/time_series/blob/master/UsingPycaret_Regression.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oxappFRWR6qm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "outputId": "476356e6-fa3f-4381-ca7b-cbca9cfd220b"
      },
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "print(tf.__version__)\n",
        "import numpy as np\n",
        "from datetime import datetime\n",
        "import statsmodels.api as sm\n",
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "import matplotlib.pyplot as plt\n",
        "import xgboost as xgb\n",
        "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
        "import imageio\n",
        "import os\n",
        "from statsmodels.graphics.tsaplots import plot_acf\n",
        "import matplotlib.pyplot as plt\n"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2.3.0\n"
          ],
          "name": "stdout"
        },
        {
          "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"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MI44fdd8Jtt5",
        "colab_type": "text"
      },
      "source": [
        "## Read Data\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UnJynIZ72ypg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "25eae995-5b7c-46e4-d2f8-ed0c4f03b0fc"
      },
      "source": [
        "from google.colab import auth\n",
        "auth.authenticate_user()\n",
        "print('Authenticated')\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Authenticated\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qeVGiMch8Wnb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "%%bigquery --project bold-sorter-281506 df2\n",
        "SELECT *\n",
        "FROM `bigquery-public-data.iowa_liquor_sales.sales`\n",
        "where store_number  = '2633'\n",
        "and date > '2018-01-01'"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SsAkQTR74wAu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "e97483a0-6398-4e56-9eca-5ebc041bca02"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "#drive.flush_and_unmount()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o-YGE2CF4vJZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#df2 = pd.read_csv('/content/drive/My Drive/data/store_2633.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sUNtTaXH_zod",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "b502e482-020d-4c5a-9b2f-ba8702da0983"
      },
      "source": [
        "df2.head(5)"
      ],
      "execution_count": 4,
      "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>invoice_and_item_number</th>\n",
              "      <th>date</th>\n",
              "      <th>store_number</th>\n",
              "      <th>store_name</th>\n",
              "      <th>address</th>\n",
              "      <th>city</th>\n",
              "      <th>zip_code</th>\n",
              "      <th>store_location</th>\n",
              "      <th>county_number</th>\n",
              "      <th>county</th>\n",
              "      <th>category</th>\n",
              "      <th>category_name</th>\n",
              "      <th>vendor_number</th>\n",
              "      <th>vendor_name</th>\n",
              "      <th>item_number</th>\n",
              "      <th>item_description</th>\n",
              "      <th>pack</th>\n",
              "      <th>bottle_volume_ml</th>\n",
              "      <th>state_bottle_cost</th>\n",
              "      <th>state_bottle_retail</th>\n",
              "      <th>bottles_sold</th>\n",
              "      <th>sale_dollars</th>\n",
              "      <th>volume_sold_liters</th>\n",
              "      <th>volume_sold_gallons</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>INV-28154300054</td>\n",
              "      <td>2020-06-22</td>\n",
              "      <td>2633</td>\n",
              "      <td>Hy-Vee #3 / BDI / Des Moines</td>\n",
              "      <td>3221 SE 14th St</td>\n",
              "      <td>Des Moines</td>\n",
              "      <td>50320</td>\n",
              "      <td>POINT (-93.596754 41.554101)</td>\n",
              "      <td>77</td>\n",
              "      <td>POLK</td>\n",
              "      <td>1012300</td>\n",
              "      <td>Single Malt Scotch</td>\n",
              "      <td>266</td>\n",
              "      <td>Edrington Group USA LLC</td>\n",
              "      <td>5486</td>\n",
              "      <td>Macallan 12YR</td>\n",
              "      <td>12</td>\n",
              "      <td>750</td>\n",
              "      <td>40.01</td>\n",
              "      <td>60.02</td>\n",
              "      <td>60</td>\n",
              "      <td>3601.20</td>\n",
              "      <td>45.0</td>\n",
              "      <td>11.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>INV-25345500055</td>\n",
              "      <td>2020-02-20</td>\n",
              "      <td>2633</td>\n",
              "      <td>Hy-Vee #3 / BDI / Des Moines</td>\n",
              "      <td>3221 SE 14th St</td>\n",
              "      <td>Des Moines</td>\n",
              "      <td>50320</td>\n",
              "      <td>POINT (-93.596754 41.554101)</td>\n",
              "      <td>77</td>\n",
              "      <td>POLK</td>\n",
              "      <td>1012300</td>\n",
              "      <td>Single Malt Scotch</td>\n",
              "      <td>266</td>\n",
              "      <td>Edrington Group USA LLC</td>\n",
              "      <td>5486</td>\n",
              "      <td>Macallan 12YR</td>\n",
              "      <td>12</td>\n",
              "      <td>750</td>\n",
              "      <td>40.01</td>\n",
              "      <td>60.02</td>\n",
              "      <td>60</td>\n",
              "      <td>3601.20</td>\n",
              "      <td>45.0</td>\n",
              "      <td>11.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>INV-16050800003</td>\n",
              "      <td>2018-12-03</td>\n",
              "      <td>2633</td>\n",
              "      <td>Hy-Vee #3 / BDI / Des Moines</td>\n",
              "      <td>3221 SE 14th St</td>\n",
              "      <td>Des Moines</td>\n",
              "      <td>50320</td>\n",
              "      <td>POINT (-93.596754 41.554101)</td>\n",
              "      <td>77</td>\n",
              "      <td>POLK</td>\n",
              "      <td>1022300</td>\n",
              "      <td>Mezcal</td>\n",
              "      <td>368</td>\n",
              "      <td>Park Street Imports</td>\n",
              "      <td>989504</td>\n",
              "      <td>Ilegal Mezcal Reposado</td>\n",
              "      <td>6</td>\n",
              "      <td>750</td>\n",
              "      <td>30.34</td>\n",
              "      <td>45.51</td>\n",
              "      <td>18</td>\n",
              "      <td>819.18</td>\n",
              "      <td>13.5</td>\n",
              "      <td>3.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>INV-21584400001</td>\n",
              "      <td>2019-08-29</td>\n",
              "      <td>2633</td>\n",
              "      <td>Hy-Vee #3 / BDI / Des Moines</td>\n",
              "      <td>3221 SE 14th St</td>\n",
              "      <td>Des Moines</td>\n",
              "      <td>50320</td>\n",
              "      <td>POINT (-93.596754 41.554101)</td>\n",
              "      <td>77</td>\n",
              "      <td>POLK</td>\n",
              "      <td>1901200</td>\n",
              "      <td>Special Order Items</td>\n",
              "      <td>497</td>\n",
              "      <td>Fredrick Wildman &amp; Son</td>\n",
              "      <td>902536</td>\n",
              "      <td>Chartreuse Yellow</td>\n",
              "      <td>12</td>\n",
              "      <td>750</td>\n",
              "      <td>31.13</td>\n",
              "      <td>46.70</td>\n",
              "      <td>24</td>\n",
              "      <td>1120.80</td>\n",
              "      <td>18.0</td>\n",
              "      <td>4.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>INV-21460600008</td>\n",
              "      <td>2019-08-26</td>\n",
              "      <td>2633</td>\n",
              "      <td>Hy-Vee #3 / BDI / Des Moines</td>\n",
              "      <td>3221 SE 14th St</td>\n",
              "      <td>Des Moines</td>\n",
              "      <td>50320</td>\n",
              "      <td>POINT (-93.596754 41.554101)</td>\n",
              "      <td>77</td>\n",
              "      <td>POLK</td>\n",
              "      <td>1012300</td>\n",
              "      <td>Single Malt Scotch</td>\n",
              "      <td>266</td>\n",
              "      <td>Edrington Group USA LLC</td>\n",
              "      <td>5486</td>\n",
              "      <td>Macallan 12 Yr Single Malt Scotch</td>\n",
              "      <td>12</td>\n",
              "      <td>750</td>\n",
              "      <td>34.99</td>\n",
              "      <td>52.49</td>\n",
              "      <td>60</td>\n",
              "      <td>3149.40</td>\n",
              "      <td>45.0</td>\n",
              "      <td>11.88</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  invoice_and_item_number        date  ... volume_sold_liters volume_sold_gallons\n",
              "0         INV-28154300054  2020-06-22  ...               45.0               11.88\n",
              "1         INV-25345500055  2020-02-20  ...               45.0               11.88\n",
              "2         INV-16050800003  2018-12-03  ...               13.5                3.56\n",
              "3         INV-21584400001  2019-08-29  ...               18.0                4.75\n",
              "4         INV-21460600008  2019-08-26  ...               45.0               11.88\n",
              "\n",
              "[5 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mpDyU--L3Wxb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df2_ds = df2[['date','sale_dollars']]\n"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H0pw8xouAEPo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df2_ds=df2_ds.sort_index(axis=0)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YbKw9JvyCjJn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "bcfce1c1-8287-494a-b33c-edc312d4c85f"
      },
      "source": [
        "df2_ds.tail(5)"
      ],
      "execution_count": 7,
      "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>date</th>\n",
              "      <th>sale_dollars</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>50522</th>\n",
              "      <td>2019-12-09</td>\n",
              "      <td>1379.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50523</th>\n",
              "      <td>2019-11-25</td>\n",
              "      <td>148.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50524</th>\n",
              "      <td>2019-10-24</td>\n",
              "      <td>119.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50525</th>\n",
              "      <td>2019-10-17</td>\n",
              "      <td>119.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50526</th>\n",
              "      <td>2019-10-21</td>\n",
              "      <td>279.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             date  sale_dollars\n",
              "50522  2019-12-09       1379.88\n",
              "50523  2019-11-25        148.50\n",
              "50524  2019-10-24        119.28\n",
              "50525  2019-10-17        119.28\n",
              "50526  2019-10-21        279.00"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FlVg7MRD6zm4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "aggregated=df2_ds.groupby('date',as_index=True).sum()"
      ],
      "execution_count": 178,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Pph6mGw7K4A",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "2079bf92-10ef-46ac-d0cd-17b5f0e31d97"
      },
      "source": [
        "aggregated.tail(5)"
      ],
      "execution_count": 179,
      "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>sale_dollars</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-07-21</th>\n",
              "      <td>22054.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-07-23</th>\n",
              "      <td>79001.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-07-27</th>\n",
              "      <td>59207.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-07-28</th>\n",
              "      <td>1905.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-07-30</th>\n",
              "      <td>117104.75</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            sale_dollars\n",
              "date                    \n",
              "2020-07-21      22054.44\n",
              "2020-07-23      79001.99\n",
              "2020-07-27      59207.67\n",
              "2020-07-28       1905.24\n",
              "2020-07-30     117104.75"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 179
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bez5t6XJ0Y59",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "aggregated.index=pd.to_datetime(aggregated.index)"
      ],
      "execution_count": 180,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2YYxAbSAAMc5",
        "colab_type": "text"
      },
      "source": [
        "#Create Fetaures"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ANeLnv9IAvgz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def create_features(df):\n",
        "    \"\"\"\n",
        "    Creates time series features from datetime index\n",
        "    \"\"\"\n",
        "    df['date'] = df.index\n",
        "    df['dayofweek'] = df['date'].dt.dayofweek\n",
        "    df['quarter'] = df['date'].dt.quarter\n",
        "    df['month'] = df['date'].dt.month\n",
        "    df['year'] = df['date'].dt.year\n",
        "    df['dayofyear'] = df['date'].dt.dayofyear\n",
        "    df['dayofmonth'] = df['date'].dt.day\n",
        "    df['weekofyear'] = df['date'].dt.weekofyear\n",
        "    df['flag'] = pd.Series(np.where(df['date'] >= np.datetime64('2020-03-03'), 1, 0), index=df.index)\n",
        "    #df['rolling_mean_7'] = df['sale_dollars'].shift(7).rolling(window=7).mean()\n",
        "    #df['lag_7'] = df['sale_dollars'].shift(7)\n",
        "    #df['lag_15']=df['sale_dollars'].shift(15)\n",
        "    #df['lag_last_year']=df['sale_dollars'].shift(52).rolling(window=15).mean()\n",
        "  \n",
        "    \n",
        "    X = df[['dayofweek','quarter','month','year',\n",
        "           'dayofyear','dayofmonth','weekofyear','flag','sale_dollars']]\n",
        "    X.index=df.index\n",
        "    return X"
      ],
      "execution_count": 176,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pq0YTx94Axo8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def split_data(data, split_date):\n",
        "    return data[data.index <= split_date].copy(), \\\n",
        "           data[data.index >  split_date].copy()"
      ],
      "execution_count": 177,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yd5OdAW5BDWv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "outputId": "beab6f5b-8ff2-4bf3-f675-d0f783fe3381"
      },
      "source": [
        "aggregated=create_features(aggregated)\n",
        "train, test = split_data(aggregated, '2020-06-15')\n",
        "\n",
        "plt.figure(figsize=(20,10))\n",
        "plt.xlabel('date')\n",
        "plt.ylabel('sales')\n",
        "plt.plot(train.index,train['sale_dollars'],label='train')\n",
        "plt.plot(test.index,test['sale_dollars'],label='test')\n",
        "plt.legend()\n",
        "plt.show()\n"
      ],
      "execution_count": 246,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "59jHH0I_CBHh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "4c55a99c-2f8f-4f6e-bf5c-6635080cfe2e"
      },
      "source": [
        "train.tail(4)"
      ],
      "execution_count": 247,
      "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>dayofweek</th>\n",
              "      <th>quarter</th>\n",
              "      <th>month</th>\n",
              "      <th>year</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofmonth</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>flag</th>\n",
              "      <th>sale_dollars</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-06-09</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>161</td>\n",
              "      <td>9</td>\n",
              "      <td>24</td>\n",
              "      <td>1</td>\n",
              "      <td>2588.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-11</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>163</td>\n",
              "      <td>11</td>\n",
              "      <td>24</td>\n",
              "      <td>1</td>\n",
              "      <td>69550.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-12</th>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>164</td>\n",
              "      <td>12</td>\n",
              "      <td>24</td>\n",
              "      <td>1</td>\n",
              "      <td>3011.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-15</th>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>167</td>\n",
              "      <td>15</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>157158.24</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            dayofweek  quarter  month  ...  weekofyear  flag  sale_dollars\n",
              "date                                   ...                                \n",
              "2020-06-09          1        2      6  ...          24     1       2588.94\n",
              "2020-06-11          3        2      6  ...          24     1      69550.07\n",
              "2020-06-12          4        2      6  ...          24     1       3011.43\n",
              "2020-06-15          0        2      6  ...          25     1     157158.24\n",
              "\n",
              "[4 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 247
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sNwbBhkkipSL",
        "colab_type": "text"
      },
      "source": [
        "# Run PyCaret"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8hz1b-ViELta",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#!pip install pycaret"
      ],
      "execution_count": 248,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0G24V-M4EWzs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from pycaret.regression import *"
      ],
      "execution_count": 249,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pb1KuIswE4Q-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 956,
          "referenced_widgets": [
            "dd2d0f5c936846a28fbc5369efa60021",
            "c6ae7158e86349fdb790d7a9b6c908d1",
            "423fcb8e2d654db394ccc98cd1c64db9"
          ]
        },
        "outputId": "5bd1fdab-70f8-44ff-ec1f-4da2c3aa8e0c"
      },
      "source": [
        "reg = setup(data = train, \n",
        "             target = 'sale_dollars',\n",
        "             numeric_imputation = 'mean',\n",
        "             categorical_features = ['dayofweek','quarter','month','year','dayofyear','dayofmonth','weekofyear',\n",
        "                                     'flag']  , \n",
        "            normalize = True, transformation = True, transform_target = True, \n",
        "                  combine_rare_levels = True, rare_level_threshold = 0.1,\n",
        "                  remove_multicollinearity = True, multicollinearity_threshold = 0.95,\n",
        "             silent = True)"
      ],
      "execution_count": 323,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " \n",
            "Setup Succesfully Completed.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style  type=\"text/css\" >\n",
              "    #T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row1_col1 {\n",
              "            background-color:  yellow;\n",
              "        }    #T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row15_col1 {\n",
              "            background-color:  yellow;\n",
              "        }    #T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row17_col1 {\n",
              "            background-color:  yellow;\n",
              "        }    #T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row23_col1 {\n",
              "            background-color:  yellow;\n",
              "        }    #T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row28_col1 {\n",
              "            background-color:  yellow;\n",
              "        }</style><table id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row0_col1\" class=\"data row0 col1\" >2927</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >Transform Target </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >True</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row2_col0\" class=\"data row2 col0\" >Transform Target Method</td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row2_col1\" class=\"data row2 col1\" >yeo-johnson</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row3_col0\" class=\"data row3 col0\" >Original Data</td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row3_col1\" class=\"data row3 col1\" >(385, 9)</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >Missing Values </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >Numeric Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >Categorical Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >8</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >Ordinal Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >High Cardinality Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >High Cardinality Method </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >Sampled Data</td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >(385, 9)</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >Transformed Train Set</td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >(269, 185)</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row12_col0\" class=\"data row12 col0\" >Transformed Test Set</td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row12_col1\" class=\"data row12 col1\" >(116, 185)</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row13_col0\" class=\"data row13 col0\" >Numeric Imputer </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row13_col1\" class=\"data row13 col1\" >mean</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row14_col0\" class=\"data row14 col0\" >Categorical Imputer </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row14_col1\" class=\"data row14 col1\" >constant</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row15_col0\" class=\"data row15 col0\" >Normalize </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row15_col1\" class=\"data row15 col1\" >True</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row16_col0\" class=\"data row16 col0\" >Normalize Method </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row16_col1\" class=\"data row16 col1\" >zscore</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row17_col0\" class=\"data row17 col0\" >Transformation </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row17_col1\" class=\"data row17 col1\" >True</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row18_col0\" class=\"data row18 col0\" >Transformation Method </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row18_col1\" class=\"data row18 col1\" >yeo-johnson</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row19_col0\" class=\"data row19 col0\" >PCA </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row19_col1\" class=\"data row19 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row20_col0\" class=\"data row20 col0\" >PCA Method </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row20_col1\" class=\"data row20 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row21_col0\" class=\"data row21 col0\" >PCA Components </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row21_col1\" class=\"data row21 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row22_col0\" class=\"data row22 col0\" >Ignore Low Variance </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row22_col1\" class=\"data row22 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row23_col0\" class=\"data row23 col0\" >Combine Rare Levels </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row23_col1\" class=\"data row23 col1\" >True</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row24_col0\" class=\"data row24 col0\" >Rare Level Threshold </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row24_col1\" class=\"data row24 col1\" >0.100000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row25_col0\" class=\"data row25 col0\" >Numeric Binning </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row25_col1\" class=\"data row25 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row26_col0\" class=\"data row26 col0\" >Remove Outliers </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row26_col1\" class=\"data row26 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row27_col0\" class=\"data row27 col0\" >Outliers Threshold </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row27_col1\" class=\"data row27 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row28_col0\" class=\"data row28 col0\" >Remove Multicollinearity </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row28_col1\" class=\"data row28 col1\" >True</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row29_col0\" class=\"data row29 col0\" >Multicollinearity Threshold </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row29_col1\" class=\"data row29 col1\" >0.950000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row30_col0\" class=\"data row30 col0\" >Clustering </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row30_col1\" class=\"data row30 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row31_col0\" class=\"data row31 col0\" >Clustering Iteration </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row31_col1\" class=\"data row31 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row32_col0\" class=\"data row32 col0\" >Polynomial Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row32_col1\" class=\"data row32 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row33_col0\" class=\"data row33 col0\" >Polynomial Degree </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row33_col1\" class=\"data row33 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row34_col0\" class=\"data row34 col0\" >Trignometry Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row34_col1\" class=\"data row34 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row35_col0\" class=\"data row35 col0\" >Polynomial Threshold </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row35_col1\" class=\"data row35 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row36_col0\" class=\"data row36 col0\" >Group Features </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row36_col1\" class=\"data row36 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row37_col0\" class=\"data row37 col0\" >Feature Selection </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row37_col1\" class=\"data row37 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row38_col0\" class=\"data row38 col0\" >Features Selection Threshold </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row38_col1\" class=\"data row38 col1\" >None</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row39_col0\" class=\"data row39 col0\" >Feature Interaction </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row39_col1\" class=\"data row39 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row40_col0\" class=\"data row40 col0\" >Feature Ratio </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row40_col1\" class=\"data row40 col1\" >False</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row41_col0\" class=\"data row41 col0\" >Interaction Threshold </td>\n",
              "                        <td id=\"T_caa3d788_dfa1_11ea_ba03_0242ac1c0002row41_col1\" class=\"data row41 col1\" >None</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803db29e48>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2i0TiH95F6E-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "f0a4a099313344e9a5e7d9f620b474be",
            "2bf03b1ea73a4b559a8f8684feecb90f",
            "825b5f03ba2c4cf890675f98b2388ef0"
          ]
        },
        "outputId": "b836020a-d314-4326-9b93-0851790015ca"
      },
      "source": [
        "# return best model\n",
        "top3 = compare_models(n_select = 3)"
      ],
      "execution_count": 206,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "            : ;\n",
              "            text-align:  left;\n",
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              "        }</style><table id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >MAE</th>        <th class=\"col_heading level0 col2\" >MSE</th>        <th class=\"col_heading level0 col3\" >RMSE</th>        <th class=\"col_heading level0 col4\" >R2</th>        <th class=\"col_heading level0 col5\" >RMSLE</th>        <th class=\"col_heading level0 col6\" >MAPE</th>        <th class=\"col_heading level0 col7\" >TT (Sec)</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col0\" class=\"data row0 col0\" >Light Gradient Boosting Machine</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col1\" class=\"data row0 col1\" >22686.3826</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col2\" class=\"data row0 col2\" >998199592.7256</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col3\" class=\"data row0 col3\" >31085.2230</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.6277</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col5\" class=\"data row0 col5\" >1.7618</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col6\" class=\"data row0 col6\" >35.9326</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.0281</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >Random Forest</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >20627.4170</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col2\" class=\"data row1 col2\" >1036362408.0806</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col3\" class=\"data row1 col3\" >31323.6236</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col4\" class=\"data row1 col4\" >0.6112</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col5\" class=\"data row1 col5\" >1.3250</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col6\" class=\"data row1 col6\" >8.4323</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0.4825</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col0\" class=\"data row2 col0\" >Extreme Gradient Boosting</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col1\" class=\"data row2 col1\" >23576.3960</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col2\" class=\"data row2 col2\" >1068494839.5553</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col3\" class=\"data row2 col3\" >32074.1424</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0.5997</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col5\" class=\"data row2 col5\" >1.6854</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col6\" class=\"data row2 col6\" >32.0353</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row2_col7\" class=\"data row2 col7\" >0.2167</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col0\" class=\"data row3 col0\" >Huber Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col1\" class=\"data row3 col1\" >23998.6184</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col2\" class=\"data row3 col2\" >1089975693.4287</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col3\" class=\"data row3 col3\" >32520.3259</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col4\" class=\"data row3 col4\" >0.5911</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col5\" class=\"data row3 col5\" >1.6243</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col6\" class=\"data row3 col6\" >25.3330</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row3_col7\" class=\"data row3 col7\" >0.1142</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >Bayesian Ridge</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >25233.7591</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col2\" class=\"data row4 col2\" >1090220468.3120</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col3\" class=\"data row4 col3\" >32691.6003</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col4\" class=\"data row4 col4\" >0.5902</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col5\" class=\"data row4 col5\" >1.7142</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col6\" class=\"data row4 col6\" >34.3396</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0.2148</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >CatBoost Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >23596.4509</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col2\" class=\"data row5 col2\" >1099383092.1949</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col3\" class=\"data row5 col3\" >32601.8867</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0.5880</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col5\" class=\"data row5 col5\" >1.6832</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col6\" class=\"data row5 col6\" >30.8476</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row5_col7\" class=\"data row5 col7\" >1.4661</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >Gradient Boosting Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >23671.0760</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col2\" class=\"data row6 col2\" >1124019242.2340</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col3\" class=\"data row6 col3\" >32787.4344</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0.5776</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col5\" class=\"data row6 col5\" >1.6721</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col6\" class=\"data row6 col6\" >31.1431</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row6_col7\" class=\"data row6 col7\" >0.1449</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >Ridge Regression</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >25610.9480</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col2\" class=\"data row7 col2\" >1156682906.4561</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col3\" class=\"data row7 col3\" >33676.5696</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0.5641</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col5\" class=\"data row7 col5\" >1.6960</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col6\" class=\"data row7 col6\" >33.1279</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row7_col7\" class=\"data row7 col7\" >0.0113</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >Passive Aggressive Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >27294.7063</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col2\" class=\"data row8 col2\" >1192216928.2732</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col3\" class=\"data row8 col3\" >34168.1735</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col4\" class=\"data row8 col4\" >0.5551</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col5\" class=\"data row8 col5\" >1.8510</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col6\" class=\"data row8 col6\" >44.7237</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row8_col7\" class=\"data row8 col7\" >0.4750</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >AdaBoost Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >27455.7249</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col2\" class=\"data row9 col2\" >1235009552.6769</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col3\" class=\"data row9 col3\" >34884.3571</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.5387</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col5\" class=\"data row9 col5\" >1.9161</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col6\" class=\"data row9 col6\" >49.7993</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row9_col7\" class=\"data row9 col7\" >0.0734</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >Orthogonal Matching Pursuit</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >25145.7780</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col2\" class=\"data row10 col2\" >1287875387.7538</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col3\" class=\"data row10 col3\" >35258.6358</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col4\" class=\"data row10 col4\" >0.5133</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col5\" class=\"data row10 col5\" >1.6252</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col6\" class=\"data row10 col6\" >24.5924</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row10_col7\" class=\"data row10 col7\" >0.0160</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >Lasso Least Angle Regression</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >26765.4268</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col2\" class=\"data row11 col2\" >1310997705.5986</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col3\" class=\"data row11 col3\" >35913.5720</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.5102</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col5\" class=\"data row11 col5\" >1.7355</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col6\" class=\"data row11 col6\" >45.0730</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row11_col7\" class=\"data row11 col7\" >0.1004</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col0\" class=\"data row12 col0\" >Extra Trees Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col1\" class=\"data row12 col1\" >23584.7235</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col2\" class=\"data row12 col2\" >1378978025.9480</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col3\" class=\"data row12 col3\" >36208.0494</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col4\" class=\"data row12 col4\" >0.4860</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col5\" class=\"data row12 col5\" >1.3636</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col6\" class=\"data row12 col6\" >1.9602</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row12_col7\" class=\"data row12 col7\" >0.5496</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col0\" class=\"data row13 col0\" >Lasso Regression</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col1\" class=\"data row13 col1\" >27580.1290</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col2\" class=\"data row13 col2\" >1419447087.6048</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col3\" class=\"data row13 col3\" >37275.1106</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col4\" class=\"data row13 col4\" >0.4659</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col5\" class=\"data row13 col5\" >1.6954</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col6\" class=\"data row13 col6\" >38.2344</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row13_col7\" class=\"data row13 col7\" >0.1108</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col0\" class=\"data row14 col0\" >TheilSen Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col1\" class=\"data row14 col1\" >28549.0721</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col2\" class=\"data row14 col2\" >1459887324.9615</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col3\" class=\"data row14 col3\" >37839.7806</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col4\" class=\"data row14 col4\" >0.4505</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col5\" class=\"data row14 col5\" >1.7363</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col6\" class=\"data row14 col6\" >41.5011</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row14_col7\" class=\"data row14 col7\" >0.0782</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col0\" class=\"data row15 col0\" >Decision Tree</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col1\" class=\"data row15 col1\" >24996.7256</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col2\" class=\"data row15 col2\" >1508073826.0623</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col3\" class=\"data row15 col3\" >38156.5929</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col4\" class=\"data row15 col4\" >0.4313</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col5\" class=\"data row15 col5\" >1.5448</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col6\" class=\"data row15 col6\" >1.8114</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row15_col7\" class=\"data row15 col7\" >0.0164</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col0\" class=\"data row16 col0\" >Elastic Net</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col1\" class=\"data row16 col1\" >39091.1634</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col2\" class=\"data row16 col2\" >1984438773.7945</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col3\" class=\"data row16 col3\" >44499.8370</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col4\" class=\"data row16 col4\" >0.2585</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col5\" class=\"data row16 col5\" >2.2058</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col6\" class=\"data row16 col6\" >71.2002</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row16_col7\" class=\"data row16 col7\" >0.0101</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col0\" class=\"data row17 col0\" >K Neighbors Regressor</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col1\" class=\"data row17 col1\" >37872.7375</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col2\" class=\"data row17 col2\" >2088025928.9233</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col3\" class=\"data row17 col3\" >45391.3615</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col4\" class=\"data row17 col4\" >0.2211</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col5\" class=\"data row17 col5\" >2.1341</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col6\" class=\"data row17 col6\" >59.2582</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row17_col7\" class=\"data row17 col7\" >0.0109</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col0\" class=\"data row18 col0\" >Support Vector Machine</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col1\" class=\"data row18 col1\" >47421.2804</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col2\" class=\"data row18 col2\" >2981414475.7721</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col3\" class=\"data row18 col3\" >54495.0699</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col4\" class=\"data row18 col4\" >-0.1174</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col5\" class=\"data row18 col5\" >2.4049</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col6\" class=\"data row18 col6\" >98.7818</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row18_col7\" class=\"data row18 col7\" >0.0477</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col0\" class=\"data row19 col0\" >Random Sample Consensus</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col1\" class=\"data row19 col1\" >94632518973712768.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col2\" class=\"data row19 col2\" >56157665614017709550287211156471808.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col3\" class=\"data row19 col3\" >169328229930207648.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col4\" class=\"data row19 col4\" >-19638582054963330747990016.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col5\" class=\"data row19 col5\" >24.5834</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col6\" class=\"data row19 col6\" >120864180794772.2031</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row19_col7\" class=\"data row19 col7\" >0.9073</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col0\" class=\"data row20 col0\" >Linear Regression</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col1\" class=\"data row20 col1\" >488567082965827520.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col2\" class=\"data row20 col2\" >847667859696169115912730805383725056.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col3\" class=\"data row20 col3\" >803237640605196544.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col4\" class=\"data row20 col4\" >-305016731497753923075178496.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col5\" class=\"data row20 col5\" >25.8551</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col6\" class=\"data row20 col6\" >442627235710059.8750</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row20_col7\" class=\"data row20 col7\" >0.0287</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col0\" class=\"data row21 col0\" >Least Angle Regression</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col1\" class=\"data row21 col1\" >422825577335357170970210842180127709522013706145234944.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col2\" class=\"data row21 col2\" >27304134247473987954563287234751405557086610359486579701583044259166150458534400298664938878537405096557281280.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col3\" class=\"data row21 col3\" >1697514095041307654985052152778152377105058534755663872.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col4\" class=\"data row21 col4\" >-10976081028902807807059415458971490047869314364097869764936783191515247371497185548350596068377886720.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col5\" class=\"data row21 col5\" >98.6265</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col6\" class=\"data row21 col6\" >9076196519438815993761511503707663006980485677056.0000</td>\n",
              "                        <td id=\"T_72a84fbe_df9c_11ea_ba03_0242ac1c0002row21_col7\" class=\"data row21 col7\" >0.2720</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803cb99b00>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BHH6Yiq1GaQo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "628922e8a1a74a02ae75ca00e1cb3345",
            "65e9354924644603ba8ab2c8ae755c09",
            "d2b8eedf273a44cb8538a4aecca9823c"
          ]
        },
        "outputId": "7984c75b-b1b8-4cab-9cab-79bb2058232c"
      },
      "source": [
        "lightgbm = create_model('lightgbm')"
      ],
      "execution_count": 324,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "            background:  yellow;\n",
              "        }</style><table id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >MAE</th>        <th class=\"col_heading level0 col1\" >MSE</th>        <th class=\"col_heading level0 col2\" >RMSE</th>        <th class=\"col_heading level0 col3\" >R2</th>        <th class=\"col_heading level0 col4\" >RMSLE</th>        <th class=\"col_heading level0 col5\" >MAPE</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row0_col0\" class=\"data row0 col0\" >17486.5188</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row0_col1\" class=\"data row0 col1\" >1316118812.7703</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row0_col2\" class=\"data row0 col2\" >36278.3518</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.5735</td>\n",
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              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >26609.1977</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >1674557218.0807</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row1_col2\" class=\"data row1 col2\" >40921.3541</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.3623</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row1_col4\" class=\"data row1 col4\" >2.0521</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row1_col5\" class=\"data row1 col5\" >12.9995</td>\n",
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              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row2_col0\" class=\"data row2 col0\" >24755.4273</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row2_col1\" class=\"data row2 col1\" >1605713011.6854</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row2_col2\" class=\"data row2 col2\" >40071.3490</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.4510</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row2_col4\" class=\"data row2 col4\" >2.0242</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row2_col5\" class=\"data row2 col5\" >7.6710</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row3_col0\" class=\"data row3 col0\" >17405.8343</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row3_col1\" class=\"data row3 col1\" >715680975.9361</td>\n",
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              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.7691</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row3_col4\" class=\"data row3 col4\" >1.0186</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row3_col5\" class=\"data row3 col5\" >2.3190</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >20478.1391</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >728201659.0991</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row4_col2\" class=\"data row4 col2\" >26985.2119</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.7159</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row4_col4\" class=\"data row4 col4\" >1.0769</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row4_col5\" class=\"data row4 col5\" >1.7815</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >23798.4458</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >1025084289.6036</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row5_col2\" class=\"data row5 col2\" >32016.9375</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.6867</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row5_col4\" class=\"data row5 col4\" >1.3147</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row5_col5\" class=\"data row5 col5\" >3.6910</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >25318.6352</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >1272138681.9004</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row6_col2\" class=\"data row6 col2\" >35667.0532</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.5258</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row6_col4\" class=\"data row6 col4\" >2.0233</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row6_col5\" class=\"data row6 col5\" >4.8183</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >27895.8593</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >1600284506.7584</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row7_col2\" class=\"data row7 col2\" >40003.5562</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.5360</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row7_col4\" class=\"data row7 col4\" >1.6094</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row7_col5\" class=\"data row7 col5\" >10.2194</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >19321.3791</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >944895515.8600</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row8_col2\" class=\"data row8 col2\" >30739.1528</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.5954</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row8_col4\" class=\"data row8 col4\" >1.7590</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row8_col5\" class=\"data row8 col5\" >14.2425</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >22869.3750</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >822404214.4126</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row9_col2\" class=\"data row9 col2\" >28677.5908</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.5728</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.6769</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.7201</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >22593.8812</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >1170507888.6107</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row10_col2\" class=\"data row10 col2\" >33811.2772</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.5788</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row10_col4\" class=\"data row10 col4\" >1.5308</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row10_col5\" class=\"data row10 col5\" >7.5680</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >3550.2647</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >354321320.5002</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row11_col2\" class=\"data row11 col2\" >5225.4593</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.1161</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.4593</td>\n",
              "                        <td id=\"T_ce83429e_dfa1_11ea_ba03_0242ac1c0002row11_col5\" class=\"data row11 col5\" >5.5202</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803cbf4828>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WYO3g_5tJ0ze",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "aa3c0811ae354670a645769a1247c272",
            "70a99c18483d485eb2222d02fe8335ee",
            "1978092cf75d4100962d83a08ec1de46"
          ]
        },
        "outputId": "239da237-7a8e-4346-cfa2-550b5b8c5b65"
      },
      "source": [
        "#%tb\n",
        "tuned_lightgbm = tune_model(lightgbm)"
      ],
      "execution_count": 325,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "        }    #T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col4 {\n",
              "            background:  yellow;\n",
              "        }    #T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col5 {\n",
              "            background:  yellow;\n",
              "        }</style><table id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >MAE</th>        <th class=\"col_heading level0 col1\" >MSE</th>        <th class=\"col_heading level0 col2\" >RMSE</th>        <th class=\"col_heading level0 col3\" >R2</th>        <th class=\"col_heading level0 col4\" >RMSLE</th>        <th class=\"col_heading level0 col5\" >MAPE</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row0_col0\" class=\"data row0 col0\" >17275.7366</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row0_col1\" class=\"data row0 col1\" >1320713887.9337</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row0_col2\" class=\"data row0 col2\" >36341.6275</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.5721</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row0_col4\" class=\"data row0 col4\" >1.7795</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row0_col5\" class=\"data row0 col5\" >19.8295</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >26792.2755</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >1554828602.8400</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row1_col2\" class=\"data row1 col2\" >39431.3150</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.4079</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row1_col4\" class=\"data row1 col4\" >2.0129</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row1_col5\" class=\"data row1 col5\" >13.3544</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row2_col0\" class=\"data row2 col0\" >25162.0842</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row2_col1\" class=\"data row2 col1\" >1521852200.1857</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row2_col2\" class=\"data row2 col2\" >39010.9241</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.4796</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row2_col4\" class=\"data row2 col4\" >1.8205</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row2_col5\" class=\"data row2 col5\" >11.7185</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row3_col0\" class=\"data row3 col0\" >20831.5704</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row3_col1\" class=\"data row3 col1\" >918218176.6272</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row3_col2\" class=\"data row3 col2\" >30302.1151</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.7038</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row3_col4\" class=\"data row3 col4\" >1.1320</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row3_col5\" class=\"data row3 col5\" >3.3920</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >15616.4694</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >547001734.7059</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row4_col2\" class=\"data row4 col2\" >23388.0682</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.7866</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row4_col4\" class=\"data row4 col4\" >1.1230</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row4_col5\" class=\"data row4 col5\" >2.6346</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >27718.5083</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >1336924351.8252</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row5_col2\" class=\"data row5 col2\" >36563.9761</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.5913</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row5_col4\" class=\"data row5 col4\" >1.2373</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row5_col5\" class=\"data row5 col5\" >4.2502</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >26832.6822</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >1325360556.8573</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row6_col2\" class=\"data row6 col2\" >36405.5017</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.5060</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row6_col4\" class=\"data row6 col4\" >2.0058</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row6_col5\" class=\"data row6 col5\" >3.7870</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >28680.3511</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >1895398063.5864</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row7_col2\" class=\"data row7 col2\" >43536.1696</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.4505</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row7_col4\" class=\"data row7 col4\" >1.6439</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row7_col5\" class=\"data row7 col5\" >11.6222</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >16011.1151</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >764352053.6389</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row8_col2\" class=\"data row8 col2\" >27646.9176</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.6727</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row8_col4\" class=\"data row8 col4\" >1.8021</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row8_col5\" class=\"data row8 col5\" >18.0479</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >22639.8447</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >851014859.9620</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row9_col2\" class=\"data row9 col2\" >29172.1590</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.5579</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.7266</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.7913</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >22756.0638</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >1203566448.8162</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col2\" class=\"data row10 col2\" >34179.8774</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.5728</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col4\" class=\"data row10 col4\" >1.5284</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row10_col5\" class=\"data row10 col5\" >8.9428</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >4781.6430</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >397412421.6857</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row11_col2\" class=\"data row11 col2\" >5941.5848</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.1134</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.4181</td>\n",
              "                        <td id=\"T_d0407066_dfa1_11ea_ba03_0242ac1c0002row11_col5\" class=\"data row11 col5\" >6.4917</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803cf32198>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d4Iatz7WKR-l",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "outputId": "ea92d629-31de-4909-9045-cd8fba9884fe"
      },
      "source": [
        "plot_model(tuned_lightgbm)"
      ],
      "execution_count": 326,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x396 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Hv6iMsZKVg0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        },
        "outputId": "ceee6d95-7f3c-4cc9-853a-a52cc9911f81"
      },
      "source": [
        "plot_model(tuned_lightgbm, plot = 'error')"
      ],
      "execution_count": 327,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x396 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "olNQjb0XKWTh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 349
        },
        "outputId": "18513181-b7cf-4b9f-b9f1-aeb2acbc3cc1"
      },
      "source": [
        "plot_model(tuned_lightgbm, plot='feature')"
      ],
      "execution_count": 328,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b_Fd_xJ1Lgs5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "outputId": "a66bbc4f-32f5-48c3-ccf6-bc079a8694dd"
      },
      "source": [
        "predict_model(tuned_lightgbm);"
      ],
      "execution_count": 329,
      "outputs": [
        {
          "output_type": "display_data",
          "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>Model</th>\n",
              "      <th>MAE</th>\n",
              "      <th>MSE</th>\n",
              "      <th>RMSE</th>\n",
              "      <th>R2</th>\n",
              "      <th>RMSLE</th>\n",
              "      <th>MAPE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Light Gradient Boosting Machine</td>\n",
              "      <td>19314.465</td>\n",
              "      <td>9.756865e+08</td>\n",
              "      <td>31235.9813</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>1.5108</td>\n",
              "      <td>0    13.150665\n",
              "dtype: float64</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             Model  ...                           MAPE\n",
              "0  Light Gradient Boosting Machine  ...  0    13.150665\n",
              "dtype: float64\n",
              "\n",
              "[1 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JV_UhNbfLifp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "final_lightgbm = finalize_model(tuned_lightgbm)"
      ],
      "execution_count": 330,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "URUPWTwkLoRs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "1545826b-2931-4642-9dc8-184f0b5a1e68"
      },
      "source": [
        "#Final Light Gradient Boosting Machine parameters for deployment\n",
        "print(final_lightgbm)"
      ],
      "execution_count": 331,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\n",
            "              importance_type='split', learning_rate=0.2, max_depth=20,\n",
            "              min_child_samples=20, min_child_weight=0.001, min_split_gain=0.3,\n",
            "              n_estimators=90, n_jobs=-1, num_leaves=20, objective=None,\n",
            "              random_state=2927, reg_alpha=0.6, reg_lambda=0.1, silent=True,\n",
            "              subsample=1.0, subsample_for_bin=200000, subsample_freq=0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s8eWLjcrLuAY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "outputId": "8e35584c-16f4-4818-9b96-4ff958b2d410"
      },
      "source": [
        "predict_model(final_lightgbm);"
      ],
      "execution_count": 332,
      "outputs": [
        {
          "output_type": "display_data",
          "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>Model</th>\n",
              "      <th>MAE</th>\n",
              "      <th>MSE</th>\n",
              "      <th>RMSE</th>\n",
              "      <th>R2</th>\n",
              "      <th>RMSLE</th>\n",
              "      <th>MAPE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Light Gradient Boosting Machine</td>\n",
              "      <td>18406.9134</td>\n",
              "      <td>9.335951e+08</td>\n",
              "      <td>30554.788</td>\n",
              "      <td>0.6779</td>\n",
              "      <td>1.4633</td>\n",
              "      <td>0    12.519468\n",
              "dtype: float64</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             Model  ...                           MAPE\n",
              "0  Light Gradient Boosting Machine  ...  0    12.519468\n",
              "dtype: float64\n",
              "\n",
              "[1 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wUpeBVkIL5zF",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "e539b6f7-0c8c-4d5e-9151-cc22eddfbaa5"
      },
      "source": [
        "unseen_predictions = predict_model(final_lightgbm, data=test)\n",
        "unseen_predictions.head()"
      ],
      "execution_count": 333,
      "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>dayofweek</th>\n",
              "      <th>quarter</th>\n",
              "      <th>month</th>\n",
              "      <th>year</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofmonth</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>flag</th>\n",
              "      <th>sale_dollars</th>\n",
              "      <th>Label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>168</td>\n",
              "      <td>16</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1376.22</td>\n",
              "      <td>3839.3983</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>170</td>\n",
              "      <td>18</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>77424.58</td>\n",
              "      <td>32710.7883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>171</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>226.68</td>\n",
              "      <td>7054.8449</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>174</td>\n",
              "      <td>22</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>97385.87</td>\n",
              "      <td>35173.8741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>176</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>3810.90</td>\n",
              "      <td>4950.3307</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   dayofweek  quarter  month  year  ...  weekofyear  flag  sale_dollars       Label\n",
              "0          1        2      6  2020  ...          25     1       1376.22   3839.3983\n",
              "1          3        2      6  2020  ...          25     1      77424.58  32710.7883\n",
              "2          4        2      6  2020  ...          25     1        226.68   7054.8449\n",
              "3          0        2      6  2020  ...          26     1      97385.87  35173.8741\n",
              "4          2        2      6  2020  ...          26     1       3810.90   4950.3307\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 333
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SzVa5sgyO3Ao",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def plot_series(time, series,i, format=\"-\", start=0, end=None):\n",
        "    #plt.figure(figsize=(20,10))\n",
        "    plt.plot(time[start:end], series[start:end], format,label=i)\n",
        "    plt.xlabel(\"Time\")\n",
        "    plt.ylabel(\"Value\")\n",
        "    plt.legend()"
      ],
      "execution_count": 334,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EiznLosEO4L3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "outputId": "032a4f05-5c57-4557-b276-be74b374bdd3"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "plot_series(test.index, test['sale_dollars'],\"True\")\n",
        "#plot_series(train['ds'],train['y'])\n",
        "plot_series(test.index, unseen_predictions['Label'],\"Predicted\")"
      ],
      "execution_count": 335,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "auWCWPD1RJOV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "huber = create_model('huber', verbose = False)\n",
        "rf = create_model('rf', verbose = False)\n",
        "lightgbm = create_model('lightgbm', verbose = False)\n",
        "ridge = create_model('ridge', verbose = False)"
      ],
      "execution_count": 336,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Wuh06ZZc5x6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "dc693a8e4e2a490e9d43f3cd82d8c47d",
            "6319427bc46444bea86b1a37d6e85318",
            "4f84347ebd0b4e03befc878084d2937d"
          ]
        },
        "outputId": "bcf59ee4-5946-4d74-f28d-caacc0dbd088"
      },
      "source": [
        "tuned_rf = tune_model(rf)"
      ],
      "execution_count": 337,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style  type=\"text/css\" >\n",
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              "                <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
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              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row0_col2\" class=\"data row0 col2\" >35015.1262</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.6027</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row0_col4\" class=\"data row0 col4\" >1.6361</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row0_col5\" class=\"data row0 col5\" >22.8205</td>\n",
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              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >26368.5144</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >1685617459.7872</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row1_col2\" class=\"data row1 col2\" >41056.2719</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.3581</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row1_col4\" class=\"data row1 col4\" >1.9108</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row1_col5\" class=\"data row1 col5\" >8.5998</td>\n",
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              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row2_col2\" class=\"data row2 col2\" >37853.4604</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.5101</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row2_col4\" class=\"data row2 col4\" >1.8223</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row2_col5\" class=\"data row2 col5\" >6.0170</td>\n",
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              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
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              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row3_col5\" class=\"data row3 col5\" >5.2372</td>\n",
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              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >15101.9106</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >460620600.8662</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row4_col2\" class=\"data row4 col2\" >21462.0735</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.8203</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row4_col4\" class=\"data row4 col4\" >1.3025</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row4_col5\" class=\"data row4 col5\" >2.6504</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >28525.0833</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >1423203144.8767</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row5_col2\" class=\"data row5 col2\" >37725.3647</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.5650</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row5_col4\" class=\"data row5 col4\" >1.1056</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row5_col5\" class=\"data row5 col5\" >1.8547</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >26246.0230</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >1254491992.5564</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row6_col2\" class=\"data row6 col2\" >35418.8085</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.5324</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row6_col4\" class=\"data row6 col4\" >1.9035</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row6_col5\" class=\"data row6 col5\" >3.0369</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >25782.4186</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >1710301522.2241</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row7_col2\" class=\"data row7 col2\" >41355.7919</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.5041</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row7_col4\" class=\"data row7 col4\" >1.4350</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row7_col5\" class=\"data row7 col5\" >6.7188</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >15568.3408</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >828448631.8387</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row8_col2\" class=\"data row8 col2\" >28782.7836</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.6453</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row8_col4\" class=\"data row8 col4\" >1.6689</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row8_col5\" class=\"data row8 col5\" >16.7581</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >23747.9651</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >954846883.2194</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row9_col2\" class=\"data row9 col2\" >30900.5968</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.5040</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.8188</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row9_col5\" class=\"data row9 col5\" >1.1211</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >21557.6699</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >1167833959.1169</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row10_col2\" class=\"data row10 col2\" >33606.3028</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.5815</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row10_col4\" class=\"data row10 col4\" >1.4858</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row10_col5\" class=\"data row10 col5\" >7.4814</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >5073.1029</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >398316294.9824</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row11_col2\" class=\"data row11 col2\" >6200.8363</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.1297</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.3469</td>\n",
              "                        <td id=\"T_e83e90a8_dfa1_11ea_ba03_0242ac1c0002row11_col5\" class=\"data row11 col5\" >6.6751</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803cf1f898>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4m9PKmv1gieh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "outputId": "b2d3c4f0-ffff-4d6f-f65a-6c5d0177267f"
      },
      "source": [
        "plot_model(tuned_rf)"
      ],
      "execution_count": 338,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x396 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R_YFuDMYelKL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "6f4b95fd6113479eb9002c8573a90bcb",
            "a04394b5c7b34b87a126c3bb19ec8f35",
            "2e4ad1847e014ce7b9e80f4ac1d0f69b",
            "f415013c0b7645ebb2c0ea2ac893b62c",
            "30973525b6724fb9aa8622d2bb8b8783",
            "a9c314b0bd1648d790d005b6938d1f08"
          ]
        },
        "outputId": "3014d3cb-db82-4380-e042-2c962502c825"
      },
      "source": [
        "xgb=create_model('xgboost')\n",
        "tuned_xbb= tune_model(xgb)"
      ],
      "execution_count": 339,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style  type=\"text/css\" >\n",
              "    #T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col0 {\n",
              "            background:  yellow;\n",
              "        }    #T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col1 {\n",
              "            background:  yellow;\n",
              "        }    #T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col2 {\n",
              "            background:  yellow;\n",
              "        }    #T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col3 {\n",
              "            background:  yellow;\n",
              "        }    #T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col4 {\n",
              "            background:  yellow;\n",
              "        }    #T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col5 {\n",
              "            background:  yellow;\n",
              "        }</style><table id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >MAE</th>        <th class=\"col_heading level0 col1\" >MSE</th>        <th class=\"col_heading level0 col2\" >RMSE</th>        <th class=\"col_heading level0 col3\" >R2</th>        <th class=\"col_heading level0 col4\" >RMSLE</th>        <th class=\"col_heading level0 col5\" >MAPE</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row0_col0\" class=\"data row0 col0\" >19157.1672</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row0_col1\" class=\"data row0 col1\" >1389753084.7128</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row0_col2\" class=\"data row0 col2\" >37279.3922</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.5497</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row0_col4\" class=\"data row0 col4\" >1.6838</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row0_col5\" class=\"data row0 col5\" >31.7928</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >31397.5453</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >2329295090.9909</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row1_col2\" class=\"data row1 col2\" >48262.7713</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.1130</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row1_col4\" class=\"data row1 col4\" >1.9810</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row1_col5\" class=\"data row1 col5\" >7.9340</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row2_col0\" class=\"data row2 col0\" >24487.0629</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row2_col1\" class=\"data row2 col1\" >1657940267.4818</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row2_col2\" class=\"data row2 col2\" >40717.8127</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.4331</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row2_col4\" class=\"data row2 col4\" >2.4513</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row2_col5\" class=\"data row2 col5\" >4.2319</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row3_col0\" class=\"data row3 col0\" >14145.1704</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row3_col1\" class=\"data row3 col1\" >491007557.8199</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row3_col2\" class=\"data row3 col2\" >22158.6903</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.8416</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row3_col4\" class=\"data row3 col4\" >1.1798</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row3_col5\" class=\"data row3 col5\" >3.3530</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >19637.9121</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >689394803.1679</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row4_col2\" class=\"data row4 col2\" >26256.3288</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.7310</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row4_col4\" class=\"data row4 col4\" >1.4846</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row4_col5\" class=\"data row4 col5\" >2.3070</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >28221.5799</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >1484049450.5221</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row5_col2\" class=\"data row5 col2\" >38523.3624</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.5464</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row5_col4\" class=\"data row5 col4\" >1.2393</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row5_col5\" class=\"data row5 col5\" >4.0709</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >29343.9412</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >1406464971.2914</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row6_col2\" class=\"data row6 col2\" >37502.8662</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.4757</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row6_col4\" class=\"data row6 col4\" >1.9363</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row6_col5\" class=\"data row6 col5\" >3.9596</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >22738.8416</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >1376901018.1453</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row7_col2\" class=\"data row7 col2\" >37106.6169</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.6008</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row7_col4\" class=\"data row7 col4\" >1.2120</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row7_col5\" class=\"data row7 col5\" >3.4116</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >20977.2641</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >1349813105.0131</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row8_col2\" class=\"data row8 col2\" >36739.8027</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.4220</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row8_col4\" class=\"data row8 col4\" >1.5122</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row8_col5\" class=\"data row8 col5\" >10.1012</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >30317.2870</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >1632107292.3057</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row9_col2\" class=\"data row9 col2\" >40399.3477</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.1521</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.7160</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.6271</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >24042.3772</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >1380672664.1451</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col2\" class=\"data row10 col2\" >36494.6991</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.4865</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col4\" class=\"data row10 col4\" >1.5396</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row10_col5\" class=\"data row10 col5\" >7.1789</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >5399.5969</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >481845543.9364</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row11_col2\" class=\"data row11 col2\" >6986.3868</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.2156</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.4704</td>\n",
              "                        <td id=\"T_039096bc_dfa2_11ea_ba03_0242ac1c0002row11_col5\" class=\"data row11 col5\" >8.5974</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803d1f2b70>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HoTVTRZqg4sA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "outputId": "bf671858-961d-4f18-8056-5ba2c4a26259"
      },
      "source": [
        "plot_model(tuned_xbb)"
      ],
      "execution_count": 340,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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41FGPC+Lr2EKhENu2bav1MdodKV9vDfWdu5bUroN/tEnI6XTicrnaODVHryMcQ2066nGBHFs86qjHBfF3bLU163e0fL21tHaXiAz4E0IIITqZdl3zr084HK7yUJh4UPkpcB1Jc49L1/U6l7UVQgjReuKy5l9WVhZ3gTT63PGO5miOKxQKVXkymxBCiGMj7qpd4XAYm83W4MNY2hvDMDrk4JajOS6n04nP5yMcDksLgBBCHENxV/O3LEsCRQdis9nirvtGCCHiXdwFf9GxyCIfQghx7EkVWggh2jHTChM0fFjKbOukiA5Egr8QQrRDlrLYsn8VuaW7CBg+AiGDxJwAQ3uNQdek0VYcnTYJ/n/4wx9Yt24d4XCYX//615x33nltkYy498knn7B8+XLKy8uZPn06Y8aMaeskCSFayJb9q9hbuAVN07Dpdiz87C3cAsCw3mPbOHWirR1tHD3mwX/16tVs376d119/naKiIi6++OK4DP4PPfQQmzdv5vDhw/j9fvr06UNKSgpPPvlkg99duXIlOTk5zJo1q8HPvvbaazzxxBOkp6fj8/mYN28eF110EQATJ05k4sSJlJSU8PDDDzc7+K9cuZIFCxZgWRYzZsxg7ty5NT7z0ksvsWTJEpRSzJgxg6uvvrpR20zT5NJLLyUzM5NnnnmmWekTorMxrTC5pbtqjInRNI3c0l0Msc7CpkvDbWfVEnH0mF89p556KiNHjgQgOTkZv9+PaZrYbLZm7c+0LHYWlLdkEhmQnoStgacp3XHHHQC8/fbbbN++ndtvv73R+x87tvGl9m3btjFv3jwuv/xyNm7cyHXXXRcL/lGLFi3il7/8ZaP3WZlpmtx333288MILZGZmMn36dCZMmMDxxx9fJQ1LlixhyZIlOBwO5syZw/jx4+nbty87duyocxvA3//+dwYMGEB5ecv+jYToyIKGj4DhqzXABww/QcNHoiu5DVLWct785mF++dN72joZcakl4ugxD/6V5+i/+eabjB07ttmBH2BnQTlDH3qvpZIHwJY7pjGoW/NurLfffpuVK1dy6NAhHnnkEe677z58Ph8+n497772XkSNHxgoMAwcOZN26dRQWFrJ7926uvfZaZsyYUWV/2dnZsRJd7969qzzsQSnFo48+ytixYxk2bFiz0rtx40b69u3LcccdB8CFF17Ip59+WiX479y5k5EjR5KQkABELrylS5dy3XXXsXv37jq35ebmsnz5cq6//npefPHFZqVPiM7I5UjE7UjEMGsuZuZ2JOByxNc6J6JltUQcbbN2o08++YQ333yT559/vsHPbtq0qcrrAQMGYBgGAD6fr8XT5vP58HobdyKDwSCGYeD1emOvc3JyePHFF9m7dy9Tp05l/PjxfP311yxatIhHH3009p1gMMjWrVt54YUX2Lt3L3feeScXXHBBlf1nZ2eTlZVFeXk5zz//PP/93/8d+61//OMfrFq1iqKiIrZv38706dNj3/vVr35V67m55ZZbOP3002Ov9+7dS0ZGRmyfqampbNq0KfYaIoWOtWvXsn//flwuF8uWLeOEE07A6/UyYMAA/u///q/Wbffddx/z5s2LLeRTeZ9RhmGwc+fORp3rtrBu3bq2TkKr6ajH1lGOyzBclJr5VZr+S0tLSbb14tsN37VhylpOR/lbtZWmxNHq2iT4f/755zz99NM899xzjXpe8fDhw2NPf4ou6xtdVS7R1/LTXxITE/F4PI36rMvlwuFwxD7vcrk46aSTSEpK4rjjjuOFF17glVdeIRAIkJSUhMfjiX3H5XJxyimnkJycTL9+/fB6vVV+9+DBg/h8Pm666Sby8vIYPHgwt956aywzmDNnDnPmzKk1Xa+//nqj02+326ukv/LxAIwYMYK5c+dyww03kJCQwLBhw3A6nXg8Hvr371/rtq+//pru3btz6qmnsmbNmiq/UVkoFGLEiBHtcvXDdevWMWrUqLZORqvoqMfWkY7LUidXGu3vJ+ANMaTvyXEx2j8YDNaotNWmo/ytWlJjz11T42h1xzz4l5WV8Yc//IEXX3yR1NTUY/3zx0S0af6ll14iMzOTRx55hLVr1/L444/X+Gx9qxVu27aN0aNH8/e//52SkhKmTJnChg0bOOWUUxpMw6xZs2qtad9+++2cddZZsdeZmZnk5ubGXufl5ZGZmVnjezNmzIh1STz22GNVPlPbtvXr1/PZZ5+xcuVKgsEg5eXl3HbbbTz66KMNpl0IAbqmM6z3WIZYZxE0fGz+fivDep/W1skS7UBLxNFjHvw/+OADioqKuPnmm2PvPfzww/Ts2fNYJ6XVFRUVMXjwYAA+++yzWFdFY2VnZ3PCCScAkJKSwpQpU1ixYkWjgv+rr77aqN8YMWIEe/bsYd++fWRmZvL+++/zxz/+scbnCgoKSE9P58CBAyxdupQ33nij3m3JycnceuutAKxZs4bnn39eAr8QzWDT7SS6ktG15o+NEh1LS8TRYx78f/GLX/CLX/ziWP9sm5g2bRq33347H374IdOnT2fp0qW89dZbjV7SNjs7u8rMgAkTJrBgwQJuueWWFkuj3W7nnnvuYc6cObFpeQMHDgTguuuu44EHHiAzM5MbbriB4uJi7HY79957L8nJRwZE1rdNCCFEy2qJOKoppVQLpafFRfs+6uvz33a4tF2N9q9L9f78juJoj6v637M96Uj9x9W11rFFl6J1ORLbZB66/M3ah9ry7urbtgbel6l+tajv3LWkuF8lYkB6ElvumNbi+xRCNF71pWjdjkSykvvHxeA0ITqjuA/+Nl1v8Vq6EKJpqi9Fa5ghWYpWiHZMiuRCiKPS0FK0phVuo5QJIeoiwV8IcVSiS9HWJroUrRDVTR/d+CXRRcuT4C+EOCrRpWhrI0vRCtE+SfAXQhwVm24nK7k/1ScOKaXISu4vT58Toh2Su1IIcdSG9oo8Tjq6FK3bkRAb7S+EaH8k+Ashjlr1pWjbap6/EKJx5O4UQrSY6FK0Qoj2TYJ/HPnkk09Yvnw55eXlTJ8+nTFjpElVCCFE08V98LeURVmgoEX32cWd3uCqZA899BCbN2/m8OHD+P1++vTpQ0pKCk8++WSjf+ejjz5i0qRJNd5/7bXXeOKJJ0hPT8fn8zFv3jwuuugiJk6cyMSJEykpKeHhhx9udvBfuXIlCxYswLIsZsyYwdy5c2v9XGlpKXfffTfbtm1D0zQWLlxIVlYW/+///T8KCgrQNI2LLrqI6667Lvadl156iSVLlqCUYsaMGVx99dXNSqMQQojWE/fBvyxQwDvraj6F7mhcPOpWUhK61fuZO+64A4C3336b7du3c/vtTZuzmpOTw/vvv19r8N+2bRvz5s3j8ssvZ+PGjVx33XVcdNFFse2LFi3il7/8ZZN+L8o0Te677z5eeOEFMjMzmT59OhMmTOD444+v8dkFCxZw9tln8/jjjxMKhQgEAgQCAe644w6GDRtGeXk5F198MePHj+f4449n27ZtLFmyhCVLluBwOJgzZw7jx4+nb9++zUqrEEKI1iFT/VqYaZrcddddzJ49m8svv5yvvvqKAwcOcO211zJ79mxmzZrF/v37ue+++/j6669rbSnIzs6mX79+APTu3RuHwwFEpk498sgjjB07lmHDhjUrfRs3bqRv374cd9xxOJ1OLrzwQj799NManysrK2Pt2rVMnz4diDx4Jzk5me7du8d+OykpiX79+pGXlwfAzp07GTlyJAkJCdjtdk499VSWLl3arHQKIYRoPXFf829v/vWvf9GtWzcWLlxIYWEhV111FZdccglnnHEGN998c6yr4Nprr+WVV15h3rx5Nfaxbds2+vXrh1KKxYsXxx7h+/LLL/PVV19RVlbGjz/+yOWXX17le7NmzcLr9dbY3+23385ZZ50FQF5eHllZWbFtmZmZbNy4scZ3cnJySEtL484772Tr1q0MGzaM3/72tyQmJlb5THZ2NieeeCIAgwYN4s9//jNFRUW43W5WrlzJ8OHDm3EWhRBCtCYJ/i1sw4YNrFu3jvXr1wORxzOeeeaZzJs3j0AgwKRJkzj55JNZs2ZNrd8/ePAgXq+XuXPnkpeXx+DBg7nhhhsAuPLKK7nyyivr/O1XX321xY4jHA7zww8/MH/+fE488UQeeOABnn32WW6++WYg8ijfG2+8kVtvvZWkpMhTEAcMGMCcOXO49tprSUhIYMiQIei6NC4JIUR7I8G/hTkcDq6//nqmTJlS5f3XXnuNb7/9lscee4xLL72UHj161Pr9bdu2MXr0aP7+979TUlLClClT2LBhA6ecckqDv92Ymn9mZia5ubmxbXl5eWRmZtb4TlZWFllZWbFa/eTJk3n22WcBMAyDG2+8kalTp3LuuedW+d6MGTOYMWMGAI899lit+xZCCNG2JPi3sBNPPJFPP/2UKVOmUFBQwEsvvcTgwYPJyMhg4sSJpKam8uGHH9KrVy/C4ZpPO8vOzuaEE04AICUlhSlTprBixYpGBf/G1PxHjBjBnj172LdvH5mZmbz//vv88Y81B0x269aNrKwsdu3aRf/+/fnqq68YMGAASil++9vf0r9/f6655poahY2CggLS09M5cOAAS5cu5Y033mgwTUIIIY4tCf4t7Pzzz2f16tXMnDkT0zSZN28eGRkZzJ8/n6SkJGw2G3fffTddu3blhx9+YOHChdx1112x72dnZzN27JHnn0+YMIEFCxbE+v2Plt1u55577mHOnDmYpsmll17KwIEDY9uvu+46HnjgATIzM5k/fz633XYbhmFw3HHH8eCDD7Ju3Tree+89Bg0axLRp07Asi9tuu41zzjkHgBtuuIHi4mLsdjv33nsvycmy4IsQQrQ3mqr+NI52JBgMsmnTJoYPH47L5QIgFAoBkdHn0Hbz/JvK6/Xi8XhadJ/twdEeV/W/Z3uybt06Ro0a1dbJaBUd9dg66nFBfB1bbXl3Y7aJY3d+4r7mr2t6g3PyhRBCCHGEDMUWQgghOhkJ/qJNteNeJyGE6LDiLvjrul7rKHkRn0zTlLUAhBDiGIu7Pn+73Y7f78fn82Gz2dA0ra2T1CiGYcQGt3UkzT0upRSmaWKaJnZ73F2GQggR1+KyytWlSxecTmfcBH6IrHvfETX3uDRNw+l00qVLlxZOkRBCiIbEbZUrHmuL7XE6W0voqMclhBAdVVzW/IUQQgjRfBL8hRBCiE5Ggr8QQgjRyUjwF0IIIToZCf5CCCFEJyPBXwghhOhkJPgLIYQQnYwEfyGEEKKTkeAvhBBCdDIS/IUQQohORoK/EEII0clI8BdCCCE6GQn+QgghRCcjwV8IIYToZCT4CyGEEJ2MBH8hhBCik5HgL4QQQnQyEvyFEEKITkaCv+gQTCuML1iKaYXbOilCCNHu2ds6AUIcDUtZbNm/itzSXQQMH25HIlnJ/Rnaawy6JmVbIYSojQR/Ede27F/F3sItaJqGTbdjmCH2Fm4BYFjvsW2cOiGEaJ+kaiTilmmFyS3dhaZpVd7XNI3c0l3SBSBEO/bmNw+3dRI6NQn+Im4FDR8Bw1frtoDhJ1jHNiGE6Owk+Iu45XIk4nYk1rrN7UjAVcc2IYTo7CT4i7hl0+1kJfdHKVXlfaUUWcn9sekypEUIIWojuaOIa0N7jQGoGO3vx+1IiI32F0IIUTsJ/iKu6ZrOsN5jGWKdRdDw4XIkSo1fiDgwffTtbZ2ETq1Nmv23bdvGxIkTWbx4cVv8vOiAbLqdRFeyBH4hRKdwtHH0mAd/n8/H/fffz5lnnnmsf1oIIYSIey0RR4958Hc6nfz1r3+le/fux/qnhRBCiLjXEnH0mLeR2u127HZpmhVCCCGaoyXiaFxE4U2bNrV1ElrEunXr2joJraKjHhfIscWjjnpc0LGOraPk6/EqLoL/8OHDcblcbZ2Mo7Ju3TpGjRrV1slocR31uECOLR511OOC+Dq2YDDYYHDvCPl6a2jMuWsJssiPEEII0ckc85r/pk2bePjhh9m/fz92u52PPvqIJ554gtTU1GOdFCGEECLutEQcPebBf/jw4bz88svH+meFEEKIDqEl4qg0+wshhBCdjAR/IYSIY6YVxhcsxbTCbZ2UJnnzm4fbOgmdWlyM9hdCCFGVpSy27NfQIpcAACAASURBVF9V8VArH25HYuyhVrom9TpRPwn+QggRh7bsX8Xewi1omoZNt2OYIfYWbgFgWO+xbZw60d5J8VAIIeKMaYXJLd2FpmlV3tc0jdzSXXHXBSCOPQn+QsSZeO3jFS0naPgIGL5atwUMP8E6tgkRJc3+QsQJ6eMVUS5HIm5HIoYZqrHN7UjA5Uhsg1SJeCLBX4g4IX28Isqm28lK7h+7HqKUUmQl98emx0fW/uKqO2L/v3rMQ22Yks5HqguiXZKm7aqkj1dUN7TXGPqkDcVhc2JaJg6bkz5pQxnaa0xbJ03EgfgoHopOQ5q2axft462tRhft4010JbdBykRb0TWdYb3HMsQ6i6Dhw+VIjJsav2h7cqWIdkWatmsnfbyiLjbdLgU/0WSdtyol2h1p2q5btI9XKVXl/Xjr4xXti3SvdV6SY4h2Q5q26xfty410ifhxOxJiXSJCNEV76V6TQX5tR4K/aDekabt+0scrWop0rwlp9hfthjRtN060j1fOh2gO6V4TIMFfNNKx6huU6UtCtC5ZHVCANPuLBjSnb9C0ws1ulpambSFal3SvCZDgLxrQUN+gpUx8wVJcjkQ0TW+xQUQyfUmI1tGeVgesvMJffWRgYMuT4C/qVF/f4MGSXVjKZG9oI4e2foPbkQgKguEAuq7LICIhKhxNS1hrqT5zxGl3k5HUm0E9zmjjlIljpX1ciaJdqm/qXbE3l4DhxSKMTU8gFA5S5M3F5UjA40qNfS46iGiIdVa7yfiEOBbay3S62kS71waZZ7Bp33IKvDkcKN5OoXd/u0mjaF3y1xV1ivYNVqeUImwZVYK5pUyUMgmFAzVG68sgItEZRbvMDDNUpSVsy/5VbZ20mG0HV5NbupuwFW63aRStQ4K/qFNdU+9MK4xNd1TpDtA1G7pmx1ImljKrfF4GEYnOJh6m08VDGkXrkeAv6lXr1LuMYXT1ZFb5nKZpOBxuNHR0zRZ7X+boi84oHqbTxUMaReuRHFnUq66pd5vRY4P5ohIdyXRN6A4asvys6FSqD+qLh+l07SGNMoq/7UjwF41SfepdNKBvLd+AaZmRQN81EuiVstrd6GYhWkN9g/ray3S6urSnKX/i2JO/rmiWaIuAL9fNsCFDqgZ6TZc5+qJTqG8djHh4EFM8pFG0Dgn+4qjomk0CveiUGhowN6TnWe1+tUpZUbPzkgF/QgjRDI0dMBcPD2KKhzSKliV/adFm2uPKZ0I0VksNmGuJ+yBe7yVZ3rftxM9VIjqMpq58FgybFHiDpHtcuOy2WvYoxLF3tAPmqt8HTnsCGUm9Gd77HBw2Z6PS0J5XERTtmwT/DiKeSv4NPSwoyrQsHl+5heU782LBf9yATG4cOxSbLhmbaHtHM2Aueh8ABIxySv355JXsZk/+RgZlntqoAN7Ye0mI6tp3lBANireSf4ODpCo9A+DxlVv45+YcdE3DZbdRHgzzz805ANwybtgxT7sQ1TV3wFzl+8AbLCZg+NAq9hcIefmx4Aeg/gDelHtJiOraX3TohEwrjC9Y2qzlNONh/fDKGjtIKhg2Wb4zD71axqZrGst35hEMm7HPHSjxxV4L0RaaOmAueh8opQiFA1S+yi1lorAaXGJXVugTR0OKhW3oaGvt7b3kX1tffWMHSRV4gxR4g7X28Rf6ghwqC/Dmd3ukS0DEpeh9EDB8WMpEo/pzMmyxAB6dSmspE1+wNK5WERTtlwT/NnS0/XX1PXK3esZxLEX76lfuOog3WI7HlcTY/j0qAnPjBkmle1yke1yUB2vWfNISXby2YTcfbNkvXQKdWDyNc6kueh/8WPADumZDKQuI3AdOpxtN03DbIwE8WknYG9rAoa3fxNUqgkdLRvm3nvi/OuJUS9Ta22vJ//GVm9met5pTMotx2QyCpoPtebt5fKXFLeNGNGqQlMtuY9yAzFiff5SlFGN+0o1Vuw/V2SXw32OGyKyADqy+FrN4Ek3vtjwvvmAJumbH6XTjcaZUCeCbc1ayt3ALFmFsekLcrSIo2icJ/m2kJWrt7XFt7mDYZF/hWvqk5AMaFjoOm0mflHz2Fa4lGD4Bl93WqEFSN44dCsDynXkU+oKkJUaa9qef2Jf3NufU2SVQ4A3SM0WaPDuq+lrMwNOmaWuK6GDBQT3OYNO+5RR4cwiGgzjtrlgA7wirCIr2Sa6SNtJStfb2VvI/XOYlxRkJ/FVppLjyOVzmpXfXSKGm+sOCqrPpOreMG8Z/jxlSZexAMGzW2yWQ7nG14BGJ9qShYJisTjiqfbdFAHXYnJz8k/Niv2+3OQmbodgDshpTSWjoXhKiOgn+baSlau1KWfTrdhIDs04jbIaanHG1dIbncZl4nCZhq3rwB4/DxONq+qh8l91WpSZfX5fAuAGZ0uTfgTUUDD3ULEw3pL1Ml9U0nd2Hv62Sju5d+uKyJxK22lfXnoh/EvzbUGNr7bUF6KPt92ytDC/Z3YVkdxIFPm+Vur8Ckt1JJLu7NHvfldXVJRB9X3RMDbWY2YzGrYxXWXtZKKe2dOQUbcNpc6GUqvLZjjSorz7R5X9l4F/L69hXTjvX0AIh9QXoo82wWivDs+l2zuh/Imt2fUNxwMAwLRw2nVS3g9P7n9himVVdXQKiY2uoxSzgb9o10F6my9aXDoWiV9pgtpd/h2mZbd61JzoGCf7tQF39dXUFaBOLw6V7amR+ljI5WLKDIT3rz7BaO8Mb3msMNmB/8a7YVL9eqa2TWVXvEhDtS2s8l6G+FrMNeRualr52Ml22vnQEwwGO73YKwdxEhg0ZIoP6RIuQK6idqi9AHyzagWEGsdscKKXwhkowjACWCqNpOhv3LePEPufW2Xzf2AyvofEAphXGUH5MK1xle6xFo6eMQO6sWvO5DC35DPpoN0IoHMRSJrpmi91zx7JPvTEDgHXNJoP6RIuRHLmdqi9AG1YQp92JVRH4gyEvmqahaTqapnOweCdOm6vO5vuGMhqH3c3mnJV1jgeo3B2RHzyMd+uOWscLyAjkzutYPJehJa4vTdNBQZE3F4WFrtlw2t0kOJLJ6tq4PvWWGDR7tAOA43nBI9E25CppQfU1cYZMiwMlvkY3f9YXoBMcHrp36cu+wmwMIxDLLBTgsrvRdb3e5vuGMpptB1fXOx6gcneErunyJDFRRUPPZWhPizBt2b+KYDiA05EQaT2zTIKGn9SE7g12U7X0oNnmTNttLzMVRPxpVPBfsWIFxcXFTJs2jVtvvZXvv/+e2267jfPOO6+109dmmtJXWV8TJ0RqQe+uy8Fcnd/o5s+GAvTQXmMImwbFvlwUCl2z4bK7SXSmAA33V9aV0QzqcQYrs1+tczzAwPBp7WKAlGi/GnouQ3tZhCnatabrOkmuVJRTxZr+0SLTaKkngDY0aLap4x2a053RXmYqtLboqP/ayEyA5mlULv3UU0+xaNEiVqxYgWVZvPPOO1x//fUdMvg3p6+yviZOgH9uzsEftuiS0LTmz/pqArqmM7LPBPK9+wmF/VX6KqHh/sq6MhpfsLTe8QBl/oJ2MUBKtF8NPZehLRdhigbk1AQb/mA+/pAXu80BRAqwNi1yXTd0LVcekxMdbBu9Bw+U7GLpjlSW78xv1niHxnZntJeZCiI+NerKcLvdpKWlsWLFCqZNm4bH40HvoE9Oa2pfZX1NnJ9uz439v/q2xjR/NlQTsOl2eqYMOKqFgqpnNA2NB+iSkF7vdjRXk7o3RMfTHhdhOlKozyUrcSd9U8vo5lEkOf047C48zpQmFZ6Dhg+/4SVoeAmFA7Hg77S7KfTpfJy9h6DpbtZ4h8b237eXmQoiPjUqggeDQZ577jk+//xzzjzzTPbs2UNZWVlrp+2Ya+wz5CuLNnHW5nB5gENlfgAsIBi2sCoW64g2f1b//dqeTV/fs8KH9hpDn7ShOGxOTMvEYXPSJ21os6fVRbsb6lpUxGl317o9bFp8d9DNZS+t4rKXVnDZSyv40/LNmJbV6N82rTC+YGm9zzAX8eHGsUP5+bDeJLnshEyTJJednw/r3aKLMNV1v9QmWqg/LmkX/boWoGsG+b4wPkMjEPLiDZXEPtuYwrPLkYgRDhAwfChloaGhlEXA8OEL+TCsqosN1ZeHRFnKYnPOSpZvXcyyrYtZvnUxm3NWYqna76FoQb02svqfaEijav73338/b7zxBg8++CAul4tVq1Zx2223tXbajlpT+9ya2lcZDJsEwyapCU78Rs2buluSG6Vge34p+WVBVImBw6aRmuBkSPeUWPPn0UyLaslpT1HVuxucdjcZSb0Z1OOMGtsty2JvUZBVP9r51w8WDns+qQlOnHZbo2s7Mmip46h8z90ybhjXnjGQHfllHJ/RhWR37avvNfU+NS2Lx5Zt5pPtuZQFDboluetd3TFaqLfrisykYqLPndCAQr+Dfl2dhMNBwvYwCc6mrZSplMIEbJqGVpE2w4SwZdW4dhsa79DU/vv2+GAvET/qvTr27dsHRJr9r7zyyth755xzTuun7Cg0N5hW76uMTKULEzRMsrokVAnWjy3/gU+2RTKf0mCIoGFyXNek2JK2llKcOzCLFTvzOFwewFIKuw6mpThcHuCEzJRYRtecaVHVM8yWnFYXe9qYeeRpYweKt1Po3U96Uj+6JY/iuIwzSPGcxAcblrO+2M6m3DJ0XWFaivyKFo3jUj2N6t7oLIOWOrLq91xaohNd07BUJOjVdg825z41LYtLX1jOF3sOY5gKh00jt9RPkS9yzY2tZfXoaKE+1R3GZTOwKjV4GqaFw56K2+nhzP7TSPVk1rHQTuR+S3LZKQ+GsWtedhUEUcrCbbew6QpLafgNnWI/bM7Nw7QSGJ6Vgt0WufbrG+8Q7b9XQChs4rDp6JpWpf8+EDbYlZ9HVnIqic7Ifo72wV6tsQhTS5LBfK2n3uB/1VVXxQa0VKdpGp9++mmrJexo1BVMw6bFL0cPqPNCj/ZVvrc5h32FZewt9hNtcNucV8Kox/7N6hsnccUrX/LF7kOELXDYNFLcDhRwuMxPaqKTtEQXZ/TN4LQ+GXy87QDdPG4Ol/swVeTz6W4XllKxJsCmTItqzcVTqmcE2w6uJrd0d8WUPhu78otYvy+X9Qc2sXxPN9x2G2X+IMkJLkJhC7t+pEZV5A+RkeQmULHPnimJtWY0MmipY6h+z23NK+WwN0C3JDfHpXpqLdA2p9D72PIf+GL3IUwVCdx+w6LYFyKvLECBN8Sp43rU+E6Sy47HaccfhqDpwGGL3HeKSI3dpmskODy1Bn5fyOAPn21i7d4CfsgtxmuYeJx2QkaIy0ZYJDqdFQV+E9PSAB1/WKM0oGNYBqv35tM3NYmeKQn1jnco9pWw7dBhSgImllIVS2I76Z2aiC/k5dnPX+dwyT6chZ8SVk5SE/ry67GXYCmNrl1G06/76aCCjW75a818RMSHeq+Szz77rM5t69ata/HEtITa+u2VUuwv9vHYyi28symHbkl1X+g3jh3Kip15rCr2U7nIo4AteaUMWPAeFmAp0LVITb7AFyLD46JvWhKPTRvFze98w59WbGHBx99jWBYpbif9kl0kejyxEn2RP0SBN0jQNDlY4sfjstcoANTWTFhfhtncde5rzwgyOCF9JyHTwqZr7CvyUewPETJNeiWXYFpdKfJbBA0TkxCmsrBjQxEZ22CYJt8fKMLjtPHyNzux6xordx2qktH8z5iBlPkPVxlxXVljBi2195pLZ1D9ngtbFgW+IJqmUewP0SslEV3TqhRooWmF3ujvfLItl7AVWTfDMC0sFAoImBbZh0v535VhVp02GpuuV7musw+VUhIIkZmYyIjMUkJmGA0TCxvZeYUkuAYwbsiRvCD63efX7GBvkZdA2MJUKtJV4AtF8oPDHk7uUYqGHmtN0LDIzk/GVDoaELagwOvnhKwUfn3WoBqDYU3L4tFlm/nLik1cNiJIgl2haeC064QtVbFPPyX+Ekwsyg1QKkDAyGbOq3+lKDi4RstKfX+n6L3y1KqtVWYklQaMFl+EqSXYbn25wc+Yf5x9DFLS8TSqSlVeXs57771HUVERAIZh8NZbb7Fq1apWTVxz1NZvn1PsI98bQFVkQPXVMMKWwh8yqdnWEZHvC+G0aSQ47LEmfg0o9oco9AWZ9rdl7Cwoj33eUlDkCxEO2zg55UgQ65rg5JV1u1ixM4+dBWXY9MhYgN6pnth+qzcTVu67dNlCBE0HVkUm89c123n/h/34jHCVPtDKhZvSQKjW/tfHlm3mnU37cNltuOw2SgIGz6/ZzC9G7Cdsapgq0pwfacZVJDoUHodJ2NKxVKSWrikNy7IImoqQaUUyZMMEBY8u20yy28FP0rrgstvwBg22533Ji19+Rs8UnfJAIfYmjriWmkvTVR5F3pKi95zTppNT7KPAF6Q0YKDrGnZdI2RauCvux8oDXesbX7O7oAyfYVa5Vgu8QcqCBnZdozxkYlW7SRXw7WEfj362idsnjoysr7FpH1vySigNGIQtxZvfezghI5eeSQYVrfGELcgt38Uzn7/J9WOno2s6j6/cwtvf7+NAmR9/2MRUR34j6pOd6WjA4AwvHqeFN2Rja76HZbsy0DUNpYGyFD9J68Ku/BJ+8dKHFPl1UhPcjD4unVvHDWX2K1+wNPsAQVORfdjDST1KUUonFLYqWtACuGxhAmEbIdMCtIriDnR1FbB6XxG9U7vUm6dVv1dSE5zsKSwnaJiUhYI4dYOAaSfZ7WbZjlyuPWMg5cFw3BSoG1NAqEwKCxGNCv4333wzPXv2ZNWqVUyaNIkvvviC3/3ud62ctOaprd++KBBC0yIZkcMWCS511TAKvEH2FZfXuu+osKUIhi2cNh1NiwR/w1Lklwf5sai8ahO2ityqXsMkbCnseiSA6prGB1v2o2saaQlODnsDHC4PAJG+8srToqIl9oBhkJW4g95ZJbhsBkHTQW55Kku+T6I4EGZ/sR+nXSe/PEiJPzIV75ZxwwiFw1z64gq+/rGAQNgk0Wnj9D4Z/GP2GJ5ctY3HVm7Bb1gV5yZS+LGUSX45JDotNC1yHlXFsZSHbHgNG1rFebSUwmbTSElwkFPRYqJrYNd17DadkoCBP2zSp2sSuqYxJH0vvVPyKQno9ExJQdOdBEJeAJJcqRWnrf5BS41tMpZlT2sfUGkYLix1cosMqIzec1tyS8j3Rq7haPkrbCkOlPj5SZoncq1XKtDWthaAZVnsyC9j3P8txW8cuVbfuGos6R4X3ZJcbDtMjcAfFbLgsRU/cNVpA/hw60E255ZQ4o/U1BVw/Wk5pCWGURzpzrRpkOYuI798O9/tXcngHj/lb2t2sKfQi2EZdHGZlIdshK2q50qhsXRnBsv3pJHoOPIZm67h0C08ThNfSKdv8m76pJbSxR0pIGwvSOLPKzJ4+sttFPqCsYLFxzvTUcCQbl6SnJH95ZUn0zu5OFKQrvjVKI/TpDxYjqWSarSsVM7TooUgw1SgRVoudhWUMqF/PoMyfHgcYcpCNrLzPXy2rRvTX1iBzwjHdYFaAnzDGpUbBoNB7rvvPmbPns3tt99OcXEx999/PxMnTmzyDy5cuJDvvvsOTdO46667GDlyZJP3UZ/qc4wN08IwFboGqQnOKs2Mhb4gB0p9uGy2WIaU7/XjDdU/1UwpCIRNDDMSGO26jtuuYSoLhVblOfZ6xZgJU0GxP0hWlwTG9c/kq70FaMC+Ii/FQYOQqTCVxf4SHwMzujDu+CwuHtGXRz7bxKrdkeby0T0P0iv5MA6bDQsdh82kmyePUb3K+WxXN2y6hmWpWAa8fGcevz5rEKf+6QO2Hy4FNDQtkiGv2JnHaX/+D11cTvxGpJbhC5mETBNVUZvfmh9p1rTUkeWDNRQ/HEokaGpoKNx2jQyPm/KQQXqikwMlkeBvqUjTbKS2AqGwRTBs4nHqsRHX3mCYTQeLMS1Fsksn0fTisntIdHrqHbTUmOVjHTZNZhBUqG1AZamZz5b9q1pkQKXLbmPMT7rx5Z7DsYKvXdMImpEm7AOlPspDBqluB9f/dHAsMEXvUyD26OeNB4vwhcIkOOyRVoOwxYqdeVz20krevXYCY/p1Z9WuQ/WmJ99ncNqf3udQWRCjUiHBbQ8zIM0PaOh61elzLptF0Ajzxc7veGWDm535JZzTr4AhGUcC8dZ8D5/sTEdR9boLmTohU8euW3R1hzjjuFKOT/eS5DBJcJg4bBaFfgeGqeG0mQzvXkzYsli6IyO2D7tukeQ0WbY7jWW700h2WVg4GdU7nUTHeuy1XLLekI1CPwRNi4SKc5rvDbI5t5hhWam47DZ8IYPnVu9gT1F5JPgT6VI4p18+IzJLUWiELZ0Eu+KkrFKUgh0FifRNS2qV5zE01d8u3tys79W3ImBt4m1gYUvE0UYFf8Mw8Pl8WJZFUVERXbt2jc0EaIqvv/6aH3/8kddff52dO3dy11138frrrzd5Pw2J9nst35lHIBwmwaHTxeWgd6on9hkFFPtC3PDW1xT5QxR7A+wr8ROo1MRXl0gQjPxPKTBMk+NSk0hNcLG/1E/l8ZGaFiksODXI8LgpC4ZZvusw2w+XYNM1CryRvtEER6S/PFwRMFftPsSiL7IpCxp0TXTRp2sC6QkFmBUFD7c9+vlIs+OXe7sd6YbQNIoCIfLKfJz39MdsPVQaeb8i2zIsC6U0duSX0aNLAgEjjKXArJRwpSLNmgBDMrx4nGasWTOSAUYKSHYNFIqbxw5lTL/unPN/S2vtMjFVJAgM6+7EZTPwhSPdA2GlKgpTNlwBnVJzBDeOrX+QX2OmZBaVfSMzCDh2AypnntKPRV9tpzxoYFiRoK9rQEWrkWVV1FkrXWP/M2YwK3bmsWZvPr5Q5BqMTpm1jDB2Tcdp1wGN1T/mUxoIMfPkfjz06SYibVR1219ac+2N7h4Dp81CaVq18B1pqbDrFnllxSxe9wPn9Cvh5B4VwVFpuB0WJ/eI3Ecf78yo8l0NxcQBkYJCr+QAboeFz7BR7HeQ7DbRtUiloMgfGdei0Bic7uWzXWmYlhb7buVCxme70uni0jmxZwZb9icwIqu0SqFDQ7E130PI1AmbFgHgUJmf8lCYeW+toVuSm7EDMvnohxy2Hi6tkt6waTA43Rvbn4qdSY0hGV7WHwxgKU+9rQkdTTyNLWipONqou37atGm88cYbzJgxgwsuuIC0tDT69OnT5B/76quvYq0FAwYMoKSkhPLycpKSkpq8r/rYdJ1bxg2LDYB7Zd0uPtiyv8oNv6+oPNIcHwpzsNTHviIfkR61xtGABIcNu66TluBkQHoXNE0j2eWg2G9QpeUfcFZ0NyQ4bIRMk9JAiGBYVWRuR/apgG/3F3FCVgplFRlikd9PpseL2x7CVJG+v2irBihSXSbpCSbFwcg4BKUU5UGTzbmllZoLI/tWCnQU4YrWiJwSf6RJv5ZjVGh8vDODZbvTYhlT9abPsIKDpX7KgwZLtx2oN0Mu9oXYVaBxem8HoXAgliitIl3FARtvbCrgv8do2Cp+prYBfQ0tH5uaYGPL/tYPeI0dbNiWgxKP1SpwKQlOBmZ0qWgRU2zPL8VlRbqKdE1jWI8U7LrOyl2HmHe2ictu4y8rtnCoPMCgbsnsK/aR7w3GCtYKjaBpEay41r0hxe8//Ja7zxuJ066T5NApMxq/gBTAIa+DkKnjsKlKBfgIywLD1PAZNspCGkMzyrHpCtOiUpCMBMdlu9Oq3AcTBxTECgZuu4WuQRenia6BTVMoNBLtJsXYY/vyOE2SnCan9qq7kLF8dwavrt/N4bJ0wqr2QjjA9sOl+A0T01KkuO24K7rBFq3KZk+Rt8Z5iP52WNXM7TxOE8sKEApbuB1Vx2m0h+cxtKX2MragpeKopmqbx1ePvLw8CgoKOOGEE5r0QwDz58/nnHPOiSV81qxZLFiwgH79+tX6+WAwyKZNm/jf//1fCgoKmvx7lZUGDAJhM9bfHq4YlGYpVWf/YX00wFGpz18Bbrst1h1QeZ8a4NA1dP3IzWZY0UF0Rz6nYv9E9m2YFm67icOm0DSFTYsGcA2HTUep6IqBCsPSMUyNYNgW25cGaFr0+BpbrGmeyG/V3RcLxI410aGwaWGOtJ9E/g2ZOoGwjRS3g5QEJ2XRv5ml0HUNt91GsjtSeyoNGPiMcOyoogUbj9NOkstGwPBGtlU/bAVuhyfyKNcGhEIhnM7aF6YprSdtzflcawoY5VQv3ilLoes6bsfRF7yjxxgyLZRSaFqk+yla9tIrxttA5O/UzePGGwpTEghVdDEdaRCo71Z02fVIYAuFUZaK9eM3RRdnGIctUmioEvwB09IImXpFwf5IodlSWuy61oCykD3WFQaKLk4TTYuEdZted4pMS4ulVymN8pCNpIrvVhfdjqZVaiyJ5BcN3c+6Fsk/QmGrjvNzJM21/W5ZKFKpiU3d1TS6JbmblIOkp6fzyCOPMHz4cFyuqmsbRPP1/7lpLofzDzdhr62nwFf7fX4s9e0aaZmu79xB0+NoXRpV/fnLX/5S472PP/6Ym266qUk/Vl1jyx2GYRAK1VxLvincOrgcOhYKFBSEmxf0K1Mqsi9FJANL0BWWDlRkFpECghbr97Yq/aCNSIZT/RREX5pWJPA7bRXtEUpDaQqtoqqslFVx/hRKRZoxnRWZWiCsk2C3sNsUOpHFRwxLIxCONKG2hmjwrY9NixSTXLodX9iKFGqI1IwMU69IX2RudcAIV9mfaSq8pkXYDJPksOHSIaxDyFSErUjXARqUBUKUBcBTMVBR1yLBp3IzcShk1GgVqEtt1125YRIMH0lc9bQ19XOtTSkNC6vKX14BytKO6r5SquIYzYrAB5hErnMFaBWBXefIta9pUOILEDDVkYCvGhfEw6ZFQCnsGoQ1mhwUAcpCNro4wW6L3DvR6yJsahgVtXlH9J6rSJWuRS4uS1UtCES2RbbXVRBRSosF2crbDUtD6yW2swAAIABJREFU11Tsu9XpmqqlMK01Ks+yFPUE/sh+DEvDaav5CcOK9NWYlootheSyg9HE68QwjCZ9Pl718LRcQT56Lzb13DWx/h7TqOBvsx3JqAzDYO3atc2q+Xfv3p38/PzY60OHDtGtW7cGv/fJJ5/UWgJqrtJAiBMeehuHblBu2CgNWLE5tXWx6xZpbguluQmZkYVBhmelxka7/3xY79igmMrNvACXvbSCg/lFdOkSWX7MUgrDVBT5gqR5XOwvicyhB/AGDRy6jsOlccXJe3DZTKID9RKdNhIdQZKcFm67TnnQJGjaKPI7MCqaWP0hnez8BE7uWV6x6AgV4VWx4WByrL/SbdNxO3QMM4zDZtTapN9UOlT08dbclpboZGSPriS57Lz8yzGc9fh/yC0tR9dCeCt+WymF06YzpEdX9hSWcUJmao1BfUkuO29cdU6s+fyRzzbxzvf7cNl19ldM6UTTGDOoIDagKSMx8ncoDgTZUZBGru/4Ro1iXrduHaNGjaryXjBsctlLK2rtcqictsZ+rrrW6CKoOto/sgqcUerivNN/0azBj9GpY59uz+WrPYdrTFO1lOJgqZ9uSS6clfIOSykuGNKTVXsOUxow2JwbGeypAF8oDCgSHXZ8FTNjonQgyWlD6TpJCU5mj+7Hip2H0FAMTNtLekIBdt2gNKCTXWlQXl13dBmRwX/dPQYFfht2XSMQ1vA4TWaNPIjbruiaYNDFeWTKr2XBwTIn6w+mVOnzt+sWV566D7cjUvDummCQ5Azj0CMBPJJXKPyGzmGvC29Ix1IaugZJzjDdPAYhS6fQ56iS3oChs2jtcYQtvdbxDXatoqUNAO1IgYtIgSTamlLX+CUfivMGFsQGJpYbNrble/hsVwYQmUFzct8MJg/p2azR/tHafX1ueHgahvI1ab+t5dp3GvHApWPU59/QuWtuHK2uUcF/3rx5VV6bpskNN9zQ5B/76U9/yhNPPMHMmTPZvHkz3bt3b/H+/oZYymJTzufMPmk3Dt3AZ9jZetjDh9u7xvrjos3Tloq0GEwaWMTgbl5SEyyCppPsw4lsPNSLsGWRllhzcQ2X3Valf2zcgExeOVyIAnKKvZHFcsIWvVITSHU72H440rcfXS0wbFokOUwSHWE0zUbYUtg0Dbuuk+hIIcNjIxQ2yPcF0XUdlx2cQNAwsbnCDO1ejkKvaPKPzj+I9Feu3d+NU3tn4nTodHFspUdSCW67QXmw6mjmaIajA43tWXXokTEAdl2LZerRsRHDs1Jj0xeT3U5mn9KPJ7/IJq8suvcjudSWvBL8RpgfC8v5SVpSlVp65f7HYNhk1e5DJDhsVaZ0AnyyI50Ut5MeScXklfuwlIND5ensLOqDovmjmBv7/IemPieiNdctqO35D99u+K7Zsx6i0ywN04oEl2pLOuuaRobHxbkDs9iwv4hCXzB2n0w/sS/vbc7BZbeRmuAk3xtEIzJjJjLTRNH7/7d35+FRlvfewL/PNltmspIFEkRAkbBZVpUdFHs8nvpaFQ9WaNW2VmvVV30P4lKX6+JoUc6xR61VjygWUCxcVG2rWK1SQRZlqSiLQaNsYUnInlmf5f1jMsNMMpnMhMksme/nurwumZkk9zMzz/N77vv+3b87z4ajTU5ougFFFGA1nb5MOX0q7pxeiTyLCYfrt6GftQ6KJMFusgOCE+MG+Gtm/O3roqiJu25VxqEmOSxZL8+iojjHizafhEaXDEkwYJG19jK7wN5ae3CePUDVxeCqGH9SnwyrosEs+N8bTRfQ4pXR5BKxt9afoHd+WQsMAA6LBrOswS5pyDWraHTLaHApwWS+wM14x8OwyCIqSxyorm9Di1uFETKp0/5xQGi/nkA3Ir4PoiTio+oSfFitIt9iwKuboBsibCagyGbGkCIH1twwvcv9GDJZLIE+nSUqjvYo60lVVRw6dCjunxs3bhxGjhyJefPmQRAEPPzwwz3582dk39FNaGg7gEKrCKdPglXR8b3+zRAF4N0Dhf5eq+HvZU8fUor/N03HVydr0eQW4dMAq6Jj5hAP/t+sfJTmT4qph3bH9EocPnIU7x914WSrG4okosRuQandilNOD6yKhHP6Ofw5BPAXJWr2uNHmlVGcI6HAZkKJ3QKT7H/+cKMHdW3+0qYQdCiiAJMkQTUMqJoEq6xC1U8HTAP+m4d+OcD9s8/F/501ES9sXIsmVzO8qgGPKoYlGn1YXQzA3wsfVGjH0cY2tHi73zkNggCpPenx7MIcf+EXWUKhzYRci9Je1e88PLVhDz75rg6yKPp7KRCCw//+PAp/fkSDywu50YmBBadXaYSuEw8NsIElne15lfDqwO4TA/HVqQp8e6oOFflFUKTTX/eeZjHHuld9vHva96TUbbwSsf9D6DJLRRKhSO3z+0BYNb+iHDPuu8S//Ch0JMOjasH3JbD6ptHlhUkSIYvAgHwb7IqM4y0uSALCPhvDMGBTJLh8Ou6Yfh7+vvczuHwFUNqzQ1s9PrR6fBhR0oY9tflo85rQ5tFh6AY8XdwIBJL1DAjwav5luQUWHwqtp5N2Nd1AQ5uC9Qf6dVrmB4SvirGbVRi6gFMuGS0euX2e3/8zg/Nd/ik7CMERAs0QIOj+4X+HSYWqCdh4sKDTTUYot6pj38lm+DSjyxtzQQAG5NkgQMDhxjb4gtUC/Uv9zJKIfjkWNLo9qHP6oEgGckz+EZwBeTb8y/D+fTLwA+mTtd9TiYqjMQX/GTNmBHtUhmGgubkZP/zhD3v0B1O5G2Bg2ZMkisi3mqAaBkzwD49NqPCiRS3CBYNKceXogRhRmo8ck4gN+1firAJ7+1C9HizPW9/2HcYMnApJ7D5wSKKIucMKUOWSkGc1BX8H4L+4uUM28gCAgQU50A0bvHobKku9kER/700QBBxuaMU/jzkgworinBPwaf410kb7pPu+WjuGFjphkf2PBfrwdouCceWluGTkeAA6zu3nxHenLGh0e6FI/lKpqm5gVKkLO2pElNhzcNOF5+CmSUNx7fKPseVgLTyaEdySOBJVN5BrkfF/p52Hn1xwbliQDlz8n9qwJxjkhhQ5IAkCjjQ5oer+5ERn+xIvh0mGZgANbi/KDVtweiW0PnpogA0NRIA/wVKRBHhUA01uEwZF+Jx6ksUc6171HV8nCjrMkg8uVcbMoeVhQS2WugXpsswq9IZLFAQUWEyoa3NDEAT4dKN9sx2EvReh72/H92Vgfg7K82zwqDp+OHog7pheiZpmJ361dhsO1Lagwe0NbuBTYDFjeGkuinLM8Pja4NOcMMunL2H5VgWK2Ib+ioZfTjqCNp8Ju2rM+LC6CGYN8HSYj7LIKkaVnN6a3IAAQxAgi4G8Gv/jsgjkWjTMGtyAv3VY5hf4ucCqmAEOD64fUwPV6Dyq4rBoEATAq/qz/wP5Caruv/k90WpGs1vCR98WQhIN2E1ql9NxbtWIuB+7KAA5igyLIqE8zwZZFFGeZ8V3DW1ocvtHHG0mGQXt+wYMhA2HGv0jCEP7OcJKn1P6SkQcjSn4v/baa8H/FwQBdrsdubmJ2UEumUKXPVXk+y9IjW4vfJoOm6Li/4wsxu3TxwaHWZ2e5uDrAz2ygHiXSTV5NDS6vJ0u4qIgwKZI8Kg6rCFJYAIMDC/JhaYfRqvbf4GyKA7sq8tH1akKAP4hvjzLKSiiF61eAd825OGj6iIIOIVRpU3+TGH4PzNJAErz/BXznJ5meFV/j7rcsAVvagDA5fXiZ1NnYnCR/+Jd0+SES9XQP9c/FOuJMIYYGrImVBRh4SWjw4aqAxf/SEFOaB9S9U8RnM4Iz2svyFTv9MLp9aEs1xZxeiU0kAQCEQQhWNBJEgUMyLV0CqxA9F3WogmtIxE6pN3xgun/t47D9Z8hz1yHHEVDrsWOC4fkQDdOb/ka7xRBKnUc0QicRw1uLwTDH4AvPrcsavCI9v5JoojBhQ5cMqw/nD4N5Qj/fs46pwxmWYIm+vey92mnE9EKrD4IhgbNEKHqEmyKgXED/OfOxu9KIKj+pYNoH+ofVdqCcwpdUHURbT4RjS4JQiCBF6dT/jTd/wUdUdyKDzss8wul6iJqWsxo9crBHIBQLR4JgiDApmiQJX+iLuD/Q5ruLxSUY9Jx+bBanJXv9s/FRykuJIsCvB1uaIT2z6jMYcasc8qw62g96p0enD+gAKP75+O9fTWwW5Sw82FQgR1uVcUzV00KFgeivi9q8H/zzTej/vCVV16Z0Mb0NrNy+oIhCEJY8LMqVlw8YmxY0Ap9fUfR6s5HkmeWuhwGHlmWj2lDSrHp25PBi+H3z6nD2fn1EEUHLIoduqHBpxpo82jBi8D+U4MgCgOhiF40uARccHYpxG++waaD/oI/Q4taYVNUqLoJ1Q2FKM4d3+m4Ot7U5NscOLe4JDiiEbjYm9qnJGqanHBpp5dKie3r6UyyiEH5OVh308yIc9QeVcOe442obfUEb3J0w0Cj2wurIkM3VFhkCZLovwVocvswqiwfw4pz8cxVkzAgzxbxohQaSEocZpgUEYLhv3mwm2XMHFoKHcBfuumpx6NjHYmupn4kUcSl5zTgu1NeqLojOLpztH4fJJwuNhTvFEEqhCYiht5wBc6j/roVs84pxX2XjAkO759ocUZ8b2J5/zreIASmjQKPd9zL3jAM+FT//gI2swNlef73+0ijE8O8bdhy2IAgSDDLIqadfRKjSlr8S28FCbJowGHWIAlG+yoAAIb/OYss+8tXixrKcgG7SUOju+tciY45AAECDHxV50/4Hde/GbouQpH9SyB9mo5Wn/932kw6RpS0QdO7Ly5kUSToPn9FzkCtDn8lUS+sJgkLZ4+EJIphycdfHGuM+D3rl2Nh4M8yUYP/J598AgBoaGjA/v37cf7550PTNOzevRtjx47NuODf8YIB+HveJklEeX7nOvKRXg90X3c+EpMkdjlcPOucMtw1cyTuaL/A5lslbPn6dfi09p3CBAGSIENQDAzKb0F1ow69fVhRN0R4NAtKHDIevnQMPqg6hhMtbnz0XQm2HCnGAIeIwpxcOCwKbCYfNF2NeOHUDQ0CRJQVhB9XaO96YEEOBuTb8EVNA1o8PiiSCJMIFORYUZFvww9HDYTNFL70JTSRrbbVjW/rW4PVFkPn6U2SGAz8AODT/FseXzGyAoOLImzSHvyMOgcSIHyqQdP9e65111OPV8fEzo5Cp5mkkHjRsdhQrFMJqRApEXH60FL824hyfFx9MuL7+dSGPZ12iPzZhWfBZrJ3+m4F3r+OezDEcoMQupd9m6cFBnTIggk55tMbRA3Mt6HZ7YbDpKHeLcIiAyNLXVDaVyF4NRlmyQcJ/l63SZIhixoEQQzeAEuCAJtiQmFOGXyaElyy2nEQTAQgigI+/KYI5XlWlNkbYZZ8aPFK2HfShg3fFqHUbsXQokYMkk/CqrghiTLsZjOONnthlnWIwTRbI5gJE1pcSNcD1wSEJ0q2t8Gf42fA49PwwuYq3DVzZNh22lMHlwT3FAlIh+9ZMkUr/ZtpZX7PRNTo9eSTTwIA7rjjDnzwwQewWCwA/Lv8Pfjgg73ful4QesEILHuKVkc+3tdH091wceBiGDrdEEoUBBTnGFBELzyaJfh44OQtsFnw00mD8d7+b+H0yf6LqAAMKzqE7/V3Y/OBKlgUG0ocgzCo+HxouopvanfB5fUPjVpNjvbtik8PSUdq95TBxTAAeHw6TjQ24uyS/C6DaWgim1WR4TApwQ2MyvNsUCT/yoCyXGswacynG7AqIn44amDMAbpjIA79/1h76okWT3W9WKcSki1SIuJf9hzBFSMr8MefzOj0fobmdFhkEQPt36ClbQdWfypgSL9+KMsdgiGlF6HB6UNRjrnbPRii3WCFrmJwepqxtfotNDbVh92oC4KA88v745YpY/BBVS10oxWFVgN5ltPTfoYBWGQNZllErsUBp7cZhqFD1QLLbAVYlVwMLh6GswoaUX2q1R/4Q/JfBAA5ZgWGYcCrAl+dGoRDzWcH8zw8qoDzy3U8c9V4DC0ywaqYsa/mE9S1HMGptuMoznHDpwswSxok0UCDWwkWJBMFAXazvypfm1eCSfIH/FafCkUQw+phmGURxXYLKvJzgnt7vLC5KngzVmgzIc+itFcOTZ/vGSVfTF3XmpqaYOAHALvdjpqaml5rVG+KtOwpWg8+3tdHE2sQijbdcHZRP8w572xs+KYuLEj8atp52HPkY4wqroZdrENtm4BDTQ7YTBIq+7UEM6sbnCdxoukg9h/bBllSoGo+OCxFkCQFoiDiSP0+iAivf99Vuz2qho+2fIZZF03scs16xzn+wBxxi8cHr6aj1GGBx6dhYPsa8dDkr/+YPapH73NXuuupJ1o800apukGJJpZExND3s+PrA7s3AgIa3QLcPg82V2/Hsk+/xqdH+qMoJ3R6S+zxHgySKMNhLcSAvKFoaAyvBGoYBgbkDcGckefjjukaalvasPdoI3TD/5n4p/1yIYsCZFFGae5gHDixHW61BZquwd8DF1FgK8GYgdNw46S9+P3mKrg8LphlJ2rbFLhUGYoktC/VNaG1fVRMNwS4VP9IlEU2MKbsOOqb3sWJ+tM3OSV5Z8Pla4NbFeD0aTDbnMgx+1fWNHnNwaWygAVDHDkw2xwwyTION7bheLMrWL7bqogotlkwqDAnOO1W7/TgiQ+/xD++ORm8eWvzasF6C9dPGJoW3zNKjZii2Lnnnot58+Zh7NixEEURn3/+eY9q+6eTeJc9JWKZVEB3QSjadIP/QjYGv5waXgxmz5GPg68fWJCL8nwDI0p80I0W2Mz+YfNWTyM83jZ/Zrbmhlttha7rcPlaoUgmmGQLbKa8Luvfd2y3WZZQbFO6vHhESmQLzBEHEoyGl+QGeybp1ONNhJ5MGyX7BiWaeBMRw1cC6MHdGwH/ipRDDW1odHtRYD4FqzIATq8Xda0HoQhy2HLOnu7BUFk+FYePHIUiecJG6YaUXoSaJn/+QUVBLpraTn8mgaBoGAYG5A/FyZaDcFgLYDfyoen+uXFJlCGIAgxDx6+mDYND/AiafhIiVHg0Ecda7Nh0eAzk9qWkeRYFTe7wKm3Dig6hsl8LdMMevMk5eGovPGobrCYH8q1mqIYHmqHALPrgsBhQIaHIZkGJ3YyKwkq8t7cRcvvqhrPyc1CRZ4Nb1fBNXQsqS/17J4TKs5iw/XB9xJu3Td/V4o4ZIxj4s1hMZ9Zjjz2GzZs3o6qqCoZh4Oc//zmmTZvW223Lat1NN3ScL+24c5soCFBkAU3OFlhN/gIQPp87+Bqf5oMB/zy/f48AHW6fv9qWbjgSsuFLtES20ASjdOvxJlIip42SLd5ExNDXmyUfzJIPevuCNFkU0eLxQQCCzwGARfKh0a0Hl3MG9GTTIVEQUawMw/eGnw+PzwlZsuB3mw5gw3sbw5IVfzVtMoDOn8mgfmNwqH6fP9gLAmTpdP5KoD1bvl4Hm1IHQZBgGCIUTcdgpRVmZQ92nZgQrGXxu01fBW9o++Uo+F5/d9iuogBgQIfL2wKLYg9ZfSS0T0Oo6GcTcXZRAQbkDUG+fRyavO+iyBp6vAJsigyHWYFP08OCv24YmDCwCB9UHcuIVSSUfFGD/969ezFixAhs3boVoihi+PDhwee2bduGiy66qNcbmIk6Ji/1RDzTDV3NLYtCIKu+fZtUQ4UgiO3JQToQXCkcqHMuwKu6kWstjmslQ1fiSWRLpx5vIiVy2ijZ4k1EDH29R1Pg0RQokj8ZzWFW0ODyQBSE4HMA4NEUSIYKn6aH/b5oq2m6O78Co3Sh+QedCyd1/kycXg8As/88gf+8EQX/8jyLYoUgiKhtORx8LwRBaN9aW8KwIjfuueQCOCw57b//9A2tVfFg84GqTvtJhJ6fkiiHrD7KhUU2Y/I5V8JmzoUkyvCoGvJMkb83I8vyMW1wMTZ9Vxs2evaLycOw62h9Wq8iodSJehV66623MGLECDz33HOdnhMEgcG/g0AN9WNNX8PpbYXNZEf/vHPOqJcXy3RDV3PLgiDAanJAQHvVPEGGvyaYf9mTAAO6oQfL/wL+C2s/e0XCAlS6JrIlWyKnjZIp3s8v9PVHW/IwtLAe+RYzBuTZ0Or1QdN1nGjND65WOdGaj0EFp4Lr+IGup0XC9yjonBwYKrbCSf7PRNP14AqFMpuK0aXHYFN0mCVAFGQoshnDyy6E09MEVfd1+lv+GwUVXl8jYDnduw/c0Gq6qdvzM7R9JklERcE5cFgLw37X+NIc7GoyIqwWKg1bLRQ6epauq0jilU1Z+MkS9Qp/3333AQBWrAjfx1jXdYhnWG+8L9p7ZCP2H98Kn+qBbqhoczei0VnbvutS7+1h0NXcsq7rGFQ0CrJsRm3zd5AlE3yaB2bZCp/mga5rgKFCEP3lzARBQo7ZgVEVMxLYtvRLZKPYxfv5hb6+rnUSapt34FTrt3D7XMiz2PDPYxZUnTqdL7S3biBGlOXBLDu7nRbZd3RT8DveXXJgPPkKoSsaFLsI3TDad+IUYG0f+TcEAQ5rEWRRCY6khZJFBQ5r5JK80XI/zi2ZEMxx6O74551XiIFt1m5XC4XizTd1Jabu3bp16+ByuTBv3jzMnz8fx48fx89//nP86Ec/6u32ZQxNV3Hg5HZ4fM72qnUiDOjw+Jw4cHI7KozezZEInVt2+ZzwqS4AQE3j17CaclDiGIRJg6/At6d2o7b5OzS0HofX8MBmyYNNyYUBHQJEDCoaAUVKfE3vvjqsny3i/fzMsoTyfDvK82dA06eEzcEfbQ0PRL+Y5q+EGG0oP1JeC9B1cmCs+QqhIwSBJEWnzwqnD1BEA6W5BZBEESebqzFiwGQUOwbiWNO3nXrSpbkDYZItnf5WQLTcD1EQY5oWkkQh7htp3nxTV2IK/m+88QZWrFiB999/H+eeey5WrVqFn/zkJwz+IZyeZri8LREvTi5vC3yyK+F/s+PcZ2BuefehD3GsqTo4OuPTvDjSUAVRkDCmYiY0XYXL24pva3fhZMvB9ouRLWMS0SizhE55dB2IxKjTIvHUTABiz1cIHSHomKTo0fz7VUji6b8xo3I+/rFvJWpbDkPVfZBFBaW5AzGjcn7U96C73I94poV6ciPNm2/qKKbgbzabYTKZ8I9//ANXXHEFh/wj6Vw6Pm6xJgpGm/sEgHpnTafPqGMPyW7Jx+iBsxKSnEgUjx4Fr25qJsiSCU5Pc9iQfCxD3qEjBD5dgqpLEMX2zaEkMZiLEEhAlEQZF4+8AV7VjRbXKTisRVF7/B1lau4H9T0xX+0fffRR7Ny5E4sXL8auXbvg9XY+CbOZzZQLq8kBp7cl7D7AAGAzOaAY1q5+NK5EJiD63Ofg4u/F1UPKhIsRb1AoWl4LRGBj1Wq4fU64vT7YjrhRWT41piFv/whBMQ6c2Ir+9kY4zE4okgqvpsCq5EFsL3/dMQHRJFtQ5ChP2vETJVpMV9KlS5finXfewY9//GNIkoSjR4/i0Ucf7e22ZRRJlHFO6UR8dWyLP5mufZmQSTLjnNKJ8J7oep4tnkSm7uY+zy2blLDNiFIt3psi6tsizZtDBDyqO1ghUIer07nT3UjDxec0wC62oNGto8VrRq5ZgN2kw2H2QJEKOB1GfVJMwb+kpASDBg3CJ598gsGDB2PMmDEYOHBgb7ct44wsnwoRQE3TN3D7WmFR7BiQNxSV5VOx68SuiD8TbyJTd3OfquaNuapcuveo47kpor6v47y5LJmwsWp1t1Nc0Wi6itrmagwssKPcMILbBwvwJ8tNGzYvrmF9okwR0xX/ySefxMGDB1FTU4P58+fjz3/+M+rr6/HrX/+6t9uXUYIXpwGxF3SJO5Ephnrx3VWVy4Qedbw3RZQ9AlNVXW2ABXRfITBw46vpavB3dNze2qepUDVvxOCf7jfORN2J6Vv72Wef4Y9//CMWLFgAALjtttswb968Xm1YJosrczdCMA9ssWuSOw/Tx1ovPlpmcSb0qOO9KaLsE8/GSQEdb3xNshVe1QWLYu90oxnpd2TCjTNRLGL6tprN/jWxgZND0zRoWudCFxS/QDA3DAO6rqPFXY+GtuNoaDuOVnc99tdshm7oYT9TWT4VZxVWQpFM0HQNimTCWYWVneYlAzchHYf6o/WoA5uZpFrgwh5JpuUuUO8IPXdCRds4KXDj69O8kEQZmu6Dpqto8zSGvU7XdRTmdE7o6/jzgRvnfUc3JfbgiHpZTD3/cePGYdGiRTh58iReeeUVvPfee5g0aVJvty1rnDdgMo43VaOmqRqa7oUAEbJkhlnOidgjP5N68ZnSo+7JjniUfTpOcYmQI94IA13f+OaY8+H2tUIWZbhVd7BA1tGGKtS3HQ327A1D51RUiizftAgAy/wmUkzf1BtuuAHbtm2D1WrF8ePHcdNNN6GykuUhE+Wrms3wqG7IogRRMAMQAEOH09cMuzm/ywtLT5bp9WSoNFUyeUc8So6ON8J7vtiPkRWROyZd3fgKggCTbMMFQ6/E18e3dyqQ1dNltETpLGrw3759O+666y54vV4UFBTghRdewKBBg7By5UosXrwYH3/8cbLa2WcFeiMG9JBNdgAIAnw+NwyTkdALSyb1qDN5RzxKrsCNcGCnvEi6vfGVbVELZPWlZbREUa+kTz31FJYvX46hQ4fi73//Ox566CHouo68vDysWbMmWW3s0wK9EVGQIAoSjJD5fd3QoBsaLIotoReWTOtRZ0IhIkp/3d34qpo3YctoidJd1G+rKIoYOnQoAODiiy/G448/jnvvvRdz5sxJSuOyQWhvxCRb4PY5gxUCRUGCADHhFxb2qClbRbvxNQz9jJfREmWKqFf8jokt/fv3Z+BPsNDeiM2UBwDwqm5ouoocswODikb02oWFPWrKNlFvfAXxjJfRUnyYwJc6cX1rO94MULieFv4I7U3ohgO51mL0s1dgVMWMXtkLfb92AAAZjklEQVRelyjbdXXjG2vPnjfOlOmiRqhdu3Zh5syZwX+fOnUKM2fOhGEYEAQBGzZs6OXmZYYzLfzBYXii9MBzkbJF1G/1+vXrk9WOjJaoinm92ZtgOVKi2LFnT31d1ChQXs4tK7uT7jXoWY6UiIg6YhfwDKWiYl48vfhMqONP1BMczcp8gcp9oZgEmBw8Y85QMivmxduLT/dRCaKeiHYeEFFsOO57hnqyuUhPxbupSGBUIpLAqARRomi6Cqenudc3h+LmOkRnjt2+BEhG4Y+e9OIzqY4/Za5k5pV0dx7kGiMS+veI+ioG/wRIxvKgnuQWZFIdf8pcycwr6e48yEHnG10i6ozD/gkUWB7UG0G1p/vbV5ZPxVmFlVAkEzRdgyKZutzylChe3fXEEz0F0N15IIFFsYhiwa5fhuhpLz5bipYw8zs1kr3apbvzwO3qelc/ygyhKwCY+d97eJXMIGeSW9BXi5awjkFqheaVGIYB3dD8G1IJQq/llUQ7D3ad2BV8HW8IibrGMyKDZEsvPh6sY5BakiijJHcIvjq2BT7NEwz+imTGef0vCvt+JioYd3ce8IaQqHvZHTkyVF/txceLdQzSgxBY5mq0/9fh8d4Kxl2dB7whJOoeb4MpY7GOQeppuooTLd/CbilAfk5p8D+7pQAnWr6FpqtJXZevG1pSExCJMhW7RTHg3GF6Yh2D1AtN+BMEAZJw+vxw+1xwepqTOjqjwZv0ctuUGEzuSy5Gsig4d5jeWMcg9bq7AYOA5K4GgIk3hEQxYASLgmVE0x/rGKRWd+WtbabcHtWn6ClRkJJWbpsok/FM6AKTyTIDV0CkXrSld6IgJn10JhnltokyHa+SXUjFVr3Uc1wBkTrd3YAlOxjzhpCoezwjusBkMqL4dHUDlqpgzBtCoq4x+HeByWREicVgTKGumXAvzGZzqpuRtRjBouDcIRER9UUM/lFw7pCIiPoiRrIYcLiSiIj6Eq7zJyIiyjIM/tQlTVfh9DSzHjoRJdza7UtS3YSsxmF/6oRljYmI+jYGf+qEW6ISEfVt7MZRmO7KGnMKgIgo8yU9+H/66ae46KKL8NFHHyX7T1MMAmWNIwmUNSYiovQTT3xNavA/dOgQXnnlFYwbNy6Zf5biEChrHAnLGhMRpad442tSg39xcTGeffZZOByOZP5ZikN3W7SyyBERJcI1E+5NdRP6lHjja1Kv5FartUc/9+WXXya4JamxY8eOVDchJoZhg6Dmok0/CdXwQhZMyBFL4PLasONE52PIlOPqCR5b5umrxwX0rWPrK9f1dBFvfO214L9mzRqsWbMm7LHbb78d06ZNi/t3jRo1KuM3gNixYwfGjx+f6mbEYQI0Xe22rHHmHVfseGyZp68eF5BZx+bxeLoN7n3hut4bYnnvEhFfey34z507F3Pnzu2tX09JwLLGRETpJxHxlUv9iKhXsEIkUfpK6pz/hg0bsGzZMlRXV2PPnj1YsWIFXn755WQ2gYh6GStEUizWbl+C66c8lOpm9BnxxtekBv+ZM2di5syZyfyTRJRkrBBJlHzxxlfehhNRwrBCJFFmYPAnooRhhUiizMDgT0QJwwqRRJmBwZ+IEoYVIokyA89EIkqoyvKpANCe7e+CRbEGs/2JAljeN7UY/IkooURBxMiK6RiuT+62QiQRpQbPSCLqFawQSZS+OOdPRESUZRj8iYiIsgyDPxERUZZh8CciIsoyDP5ERERZhsGfiIgoyzD4ExERZRkGfyIioizD4E9ERJRlGPyJiIiyDIM/ERFRlmHwJyIiyjIM/kRERFmGwZ+IiCjLMPhTj2m6Cp/hgqarqW4KERHFQU51Ayjz6IaOfUc34XhzNeo8tWjb/zXKcoegsnwqRIH3k0RE6Y7Bn+K27+gmHKrfB0EQIAoifJoXh+r3AQBGVkxPceuIiKg77KZRXDRdxfHmagiCEPa4IAg43lzNKQAiogzA4E9x8ficcPucEZ9z+1zwdPEcEVGotduXpLoJWY3Bn+JiVmywKLaIz1kUK8xdPEdEROmDwZ/iIokyynKHwDCMsMcNw0BZ7hBIItNIiIjSHa/UFLfK8qkAgOPN1dANHYpkCmb7ExFR+mPwp7iJgoiRFdMxXJ+Mz3ZuxcThF7LHT0SUQTjsTz0miTIUwcrAT0SUYRj8iYiIsgyDP/UaTVfh9DRz7T8RUZrheC0lXGj5X7fPCYtiY/lfIqI0wuBPCRda/lcSZZb/JSJKM+yGUUKx/C8RUfpj8KeEYvlfIorFNRPuTXUTshqDPyUUy/8SEaU/Bn9KKJb/JSJKf7wSU8KFlv91+1ywKFaW/yUiSiMM/pRwoeV/PT4nzIqNPX4iojTCKzL1GkmUYTPnproZRETUAef8iYgo6dZuX5LqJmQ19vx7maar8Pic0A0t1U0hIiICwODfazqWuHV7fbAdcbPELRERpRyDfy/pWOJWh4slbomIKC2wC9oLWOKWiIjSGYN/L2CJWyKi6FjeN7UY/HsBS9wSEVE6Y/DvBSxxS0RE6YxRqJd0LHErQsZZhZUscUtERCnH4N9LOpa43fPFfoysmJTqZhEREXHYv7cFStyKgpTqphAREQFg8CciIso6SR32V1UVDzzwAA4dOgRN07Bw4UJMmDAhmU0gIiLqc+KNr0kN/m+99RasVitef/11HDhwAPfddx/Wrl2bzCYQERH1OfHG16QG/yuuuAL/9m//BgAoLCxEY2NjMv88ERFRnxRvfE1q8FcUJfj/r776arChRERE1HPxxlfB6FiJJkHWrFmDNWvWhD12++23Y9q0aVi1ahU+/PBDPP/882EN7sjj8eDLL7/sjeYREVEvGzVqFMxmc9hjvK7HJtJ7F5CI+Nprwb8ra9aswfr16/Hcc891eWABgS9JtDchU+zYsQPjx49PdTMSrq8eF8Bjy0R99biAzDq2aNfuvnRd7w1n8v7EE1+TOux/+PBhrF69GitXruSHTkRElCDxxtekBv81a9agsbERN998c/CxZcuWwWQyJbMZREREfUq88TWpwf/uu+/G3Xffncw/SURE1OfFG19Z4Y+IiCjLMPgTERFlGQZ/IiKiLMPg34dpugqnpxmarqa6KURElEaSmvBHyaEbOvYd3YTjzdVw+5ywKDaU5Q5BZflUiALv94iIsh2Dfx+07+gmHKrfB0EQIIkyfJoXh+r3AQBGVkxPceuIiCjVGPz7GE1Xcby5GoIghD0uCAKON1djuD4ZksiPnYhSa+32JfAZzuC/b5j6mxS2JvtwDLiP8ficcPucEZ9z+1zwdPEc8wOIiLIHu4B9jFmxwaLY4NO8nZ6zKFaYFVvYY8wPICLKPry69zGSKKMsdwg67tdkGAbKcod0GvIP5Af4NG9YfsC+o5uS2WwiIkoiBv8+qLJ8Ks4qrIQimaDpGhTJhLMKK1FZPjXsdd3lB3AKgIiob+Kwfx8kCiJGVkzHcH0yPD4nzIotYpJfID8g0nOB/ACbOTcZTSaiLHPNhHu5u2sKseffh0miDJs5t8vs/kB+QCSR8gOIiKhvYPDPYvHmBxARUd/Aq3uWC+QB+LP9XbAo1mC2PxER9U0M/lku1vwAIiLqO3iVJwCn8wOIiKjv45w/ERFRlmHwJyIiyjIM/kRERFmGwZ+IiCjLMPgTERFlGQZ/IiKiLMPgT0RElGXSep1/oOys19t5b/pM5PF4Ut2EXtFXjwvgsWWivnpcQOYcW+Ca3bF0eOhjfeW6nmjR3rtEEoze/gtnoKWlBVVVValuBhER9cCwYcPgcDjCHuN1PTaR3rtESuvgr+s62traoChKpz3niYgoPRmGAZ/Ph5ycHIhi+Owyr+vRRXvvEimtgz8RERElHhP+iIiIsgyDPxERUZZh8CciIsoyDP5ERERZJq3X+WeyTz/9FHfeeScee+wxzJo1q9PzI0eOxLhx44L/Xr58OSRJSmYTe6y7Y3v77bfx6quvQhRFXHvttZg7d24KWhk/n8+HRYsWoaamBpIk4fHHH8fAgQPDXpNpn9tjjz2Gzz//HIIg4P7778eYMWOCz23evBn//d//DUmSMH36dNx2220pbGn8oh3b7NmzUVZWFvxsli5ditLS0lQ1NW5VVVX45S9/iRtuuAHz588Pe64vf27p6IknnsCOHTugqip+8YtfYPTo0Vi4cCE0TUNxcTGefPJJmEymVDczfgYl3MGDB41bbrnF+OUvf2l8+OGHEV8zadKkJLcqMbo7tra2NuPSSy81mpubDZfLZVx++eVGQ0NDCloav3Xr1hmPPPKIYRiGsXHjRuPOO+/s9JpM+ty2bdtm3HzzzYZhGMbXX39tXHvttWHPX3bZZUZNTY2haZpx3XXXGQcOHEhFM3uku2ObNWuW0dramoqmnbG2tjZj/vz5xoMPPmisWLGi0/N9+XNLN1u2bDF+9rOfGYZhGPX19caMGTOMRYsWGe+8845hGIbxX//1X8aqVatS2cQe47B/LyguLsazzz7bqwUaUqW7Y/v8888xevRoOBwOWCwWjBs3Djt37kxyK3tmy5YtmDNnDgBg8uTJGdPurmzZsgWXXHIJAGDo0KFoampCa2srAODw4cPIy8tD//79IYoiZsyYgS1btqSyuXGJdmyZzmQy4X//939RUlLS6Tl+bsk1ceJE/M///A8AIDc3Fy6XC9u2bcPFF18MAJg1a1ZGvf+hGPx7gdVq7XYo2Ov14p577sG8efPwyiuvJKllZ667Y6urq0NhYWHw34WFhaitrU1G085YaNtFUYQgCJ1KkGbS51ZXV4eCgoLgv0M/i9ra2oz9nIDoxxbw8MMP47rrrsPSpUt7vVRqIsmyDIvFEvG5bPjc0okkSbDZbACAtWvXYvr06XC5XMFh/qKiorRufzSc8z9Da9aswZo1a8Ieu/322zFt2rSoP7dw4UJcccUVEAQB8+fPx4QJEzB69OjebGrcenpsodL1ohvp2D7//POwf0dqeyZ8bl1J188iEToe2x133IFp06YhLy8Pt912G9577z38y7/8S4paR13JlO/kBx98gLVr1+Lll1/GpZdeGnw8U9ofCYP/GZo7d26PEtquu+664P9feOGFqKqqSrsg0pNjKykpQV1dXfDfJ0+exPe+971EN+2MRTq2RYsWoba2FsOHD4fP54NhGJ0SeTLhcwuI9FkUFxdHfO7EiRMRh5nTVbRjA4Arr7wy+P/Tp09HVVVVnwj+ff1zS0cbN27E888/j5deegkOhwM2mw1utxsWiyXj3v9QHPZPgerqatxzzz0wDAOqqmLnzp0499xzU92shDj//PPxxRdfoLm5GW1tbdi5cycmTJiQ6mbFZMqUKVi/fj0A4KOPPsIFF1wQ9nymfW5TpkzBe++9BwDYs2cPSkpKYLfbAQAVFRVobW3FkSNHoKoqPvroI0yZMiWVzY1LtGNraWnBT3/60+CUzWeffZbWn1M8+vLnlo5aWlrwxBNP4IUXXkB+fj4Afz5Q4Bj+9re/xTUSmk5Y278XbNiwAcuWLUN1dTUKCwtRXFyMl19+GS+++CImTpyIsWPH4sknn8TWrVshiiJmz56NW2+9NdXNjkksx7Z+/XosW7YsODR+xRVXpLrZMdE0DQ8++CC+++47mEwm/OY3v0H//v0z+nNbunQptm/fDkEQ8PDDD2Pv3r1wOByYM2cOPvvsMyxduhQAcOmll+KnP/1pilsbn2jH9uqrr+LNN9+E2WzGiBEj8Otf/zpjNpH58ssvsWTJEhw9ehSyLKO0tBSzZ89GRUVFn/zchg8fnuomdemNN97AM888g8GDBwcf+81vfoMHH3wQHo8HAwYMwOOPPw5FUVLYyp5h8CciIsoyHPYnIiLKMgz+REREWYbBn4iIKMsw+BMREWUZBn8iIqIsw+BPfd6RI0cwatQoLFiwAAsWLMC8efNwzz33oLm5uce/c82aNVi0aBEA4K677sKJEye6fO3OnTtx+PDhmH+3qqo477zzwh5rbW3FxIkTUV9fH/b4jh078P3vf7/L3zV79mwcPHgw5r9NlC4inbdLly6Fy+XCxx9/jN///vdRf/6tt96K+Pi6deuC1T3PO+88qKoac5u+/vpr7NmzBwDw4osvYsOGDTH/bLph8KesUFhYiBUrVmDFihVYvXo1SkpKur14xOqpp56Kul3sunXr4gr+kdjtdlxyySX4y1/+Evb4m2++iauvvvqMfjdRugo9b1999VW0tbXhnnvuwfTp06PW2Dhx4gRWr14d8bmrrrqqx9uMv//++9i7dy8A4Oabb8bMmTN79HvSAcv7UlaaOHEi3njjDQD+3vFll12Gw4cP4+mnn8Y777yDlStXwjAMFBYWYvHixSgoKMCqVavw+uuvo6ysLKyk5+zZs/HKK69g4MCBWLx4Mb788ksAwI033ghZlrF+/Xrs3r0b9913HwYNGoRHH30ULpcLTqcTd999NyZPnozq6mr8x3/8B6xWa6fKggFXX301HnvsMfz4xz8GAHg8Hrz//vv485//jNdeew1vvfUWFEWB2WzGU089hdzc3ODPrlu3Dps3bw4Wh1mwYAFuvfVWTJ48GStWrMC7774LTdMwZMgQPPzww11uLEOUKmazGffffz++//3vY9WqVdi1axeWLl2KpUuXYuvWrTCZTCgtLcWSJUtwzz33oKqqCgsXLsTVV1+N5557DmazGXPmzMHx48ehqiruuusuAMDzzz+PrVu3oq2tDUuWLMGwYcOC5/SgQYOwbds2/Pa3v8XChQuxcuVK2O12WCwWfPLJJxg/fjzmzp2LtWvXYvXq1bBarSgqKsLixYtht9sxfvx43HLLLdi4cSNqa2vx29/+ttOoXqqw509ZR9M0vP/++xg/fnzwsbPPPhtPP/00jh07hueffx7Lly/H66+/jkmTJuGFF15AS0sLnn76aaxYsQIvvfQSGhoaOv3et99+G3V1dfjjH/+Il156CX/6058we/ZsVFZWYtGiRbjooovwyCOP4MYbb8Qf/vAH/P73v8eDDz4IVVXxu9/9DldffTVWrlzZ5cVhwoQJcDqdqKqqAgD8/e9/x9ixY1FcXAyPx4Nly5Zh5cqVKC8vx9tvvx3Te7F79268//77WLVqFd544w04HI5OGx4RpQtFUTBq1Ci0tbUBAJqamoLf3ddeew1z5sxBXV0dbr/9dgwbNgxPPPEEAH/VxCeeeCJij3/o0KFYuXIlfvSjH+HZZ5/t8m+PHTsW06ZNw89+9jP84Ac/CD5eU1ODZ555BsuXL8eKFSvQv39/LF++HIB/um7YsGH4wx/+gMsvvzytzi32/Ckr1NfXY8GCBQAAXdcxYcIE3HDDDcHnx44dCwDYtWsXamtrgyVTvV4vKioqcPDgQZSXlwe3I73ggguwf//+sL+xe/fuYK89NzcXL774Yqd2bNu2DW1tbfjd734HwL9966lTp1BVVYWbb74ZgH/DoK5cffXV+NOf/oR7770Xb775Jv793/8dAJCfn4+bb74Zoiji6NGjMW+Wsm3bNhw6dCg4muB0OiHLvCxQ+mppaQluK56Xl4dp06Zh/vz5mDNnDv71X/8VZWVlnabZBg8eHKzN31Fgb4Rx48bh5Zdfjrs9e/fuxciRI4N7FEyaNClsyiFwPg8YMCCt8m94llNWCMwddiVQm9tkMmHMmDF44YUXwp7/4osvwmrD67re6XcIghDx8VAmkwnPPPNM2J7sgH9rUFH0D8Rpmtblz1955ZWYO3cubrzxRnz11VeYMWMGjh8/jiVLluCvf/0rioqKsGTJkohtC+Xz+YLtmT17Nh566KGo7SZKBy6XC/v27cPll18efOzpp5/GN998g3/84x+YP38+nnnmmU4/F632fuC8Mwwj4v4PgXMlVh1/T+BGJfBcuuCwP1GI0aNHY/fu3aitrQUAvPvuu/jggw9w1lln4ciRI2huboZhGNiyZUunnx07diw2btwIwD/cN3fuXHi9XgiCELyAjB8/Hu+++y4A/2jEf/7nfwLwDz3+85//BICIvzuguLgYI0aMwJIlS/CDH/wgOHJQUFCAoqIiNDY2YtOmTcEd7QLsdjuOHz8OADh16hQOHDgAwN/b+fjjj4PDqIG5VKJ04/P5sHjxYkyZMiUYsA8fPozly5dj6NChuOmmmzBnzhzs378foijGnMUfON927tyJYcOGAfCfL8eOHQMAbN26Nfja0HM5YNSoUdizZw9aW1sBAJs3b8b5559/ZgebBOz5E4UoLS3FAw88gF/84hewWq2wWCxYsmQJ8vLycMstt+D6669HeXk5ysvL4Xa7w372sssuw86dOzFv3jxomoYbb7wRJpMJU6ZMwcMPP4z7778fDzzwAB566CH89a9/hdfrDWYs33bbbbj33nuxfv16jB07NurQ+zXXXINbb701uP1wZWUlBg0ahGuuuQZnnXUW7rjjDjzyyCOYMWNG8GemTJmCZcuW4dprr8XQoUOD0xyjR4/G9ddfjwULFsBsNqOkpARXXXVVot9Woh4JTNdpmobm5mZMmTIleP4A/vN17969uOaaa5CTk4O8vDz86le/gtfrxalTp3DjjTfilltu6fL3S5KEAwcOYPXq1WhoaMCTTz4JALjpppvwwAMP4Oyzz8a4ceOCr7/wwgvxxBNPhPXgy8rKcOeddwbP97KyMtx999299I4kDnf1IyIiyjIc9iciIsoyDP5ERERZhsGfiIgoyzD4ExERZRkGfyIioizD4E9ERJRlGPyJiIiyDIM/ERFRlvn/W0APBXayq1YAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x396 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tkvnGBfdTrGr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292,
          "referenced_widgets": [
            "0b0a16cfa95445aeb3701ce7234fe1b4",
            "e7a04df440904360b4a9b7137438e7d5",
            "ab58327fbd5a46b295cd621089080b92"
          ]
        },
        "outputId": "9e4abecb-c41c-4cc1-b6a7-a3d1c50a3a03"
      },
      "source": [
        "blend_specific = blend_models(estimator_list = [tuned_rf,dt,tuned_lightgbm,tuned_xbb])"
      ],
      "execution_count": 341,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style  type=\"text/css\" >\n",
              "    #T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col0 {\n",
              "            background:  yellow;\n",
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              "            background:  yellow;\n",
              "        }    #T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col2 {\n",
              "            background:  yellow;\n",
              "        }    #T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col3 {\n",
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              "            background:  yellow;\n",
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              "            background:  yellow;\n",
              "        }</style><table id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >MAE</th>        <th class=\"col_heading level0 col1\" >MSE</th>        <th class=\"col_heading level0 col2\" >RMSE</th>        <th class=\"col_heading level0 col3\" >R2</th>        <th class=\"col_heading level0 col4\" >RMSLE</th>        <th class=\"col_heading level0 col5\" >MAPE</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row0_col0\" class=\"data row0 col0\" >16538.2706</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row0_col1\" class=\"data row0 col1\" >1330748346.0612</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row0_col2\" class=\"data row0 col2\" >36479.4236</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.5688</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row0_col4\" class=\"data row0 col4\" >1.6560</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row0_col5\" class=\"data row0 col5\" >20.2704</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row1_col0\" class=\"data row1 col0\" >27246.4834</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row1_col1\" class=\"data row1 col1\" >1715456413.3190</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row1_col2\" class=\"data row1 col2\" >41418.0687</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.3467</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row1_col4\" class=\"data row1 col4\" >1.9783</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row1_col5\" class=\"data row1 col5\" >11.0350</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row2_col0\" class=\"data row2 col0\" >23394.5133</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row2_col1\" class=\"data row2 col1\" >1486325000.7813</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row2_col2\" class=\"data row2 col2\" >38552.8858</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.4918</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row2_col4\" class=\"data row2 col4\" >1.8523</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row2_col5\" class=\"data row2 col5\" >5.0704</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row3_col0\" class=\"data row3 col0\" >15829.3938</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row3_col1\" class=\"data row3 col1\" >693244770.5407</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row3_col2\" class=\"data row3 col2\" >26329.5418</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.7764</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row3_col4\" class=\"data row3 col4\" >1.0098</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row3_col5\" class=\"data row3 col5\" >2.1860</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row4_col0\" class=\"data row4 col0\" >14503.4533</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row4_col1\" class=\"data row4 col1\" >450433334.0641</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row4_col2\" class=\"data row4 col2\" >21223.4148</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.8242</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row4_col4\" class=\"data row4 col4\" >1.3015</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row4_col5\" class=\"data row4 col5\" >2.4366</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row5_col0\" class=\"data row5 col0\" >26237.6855</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row5_col1\" class=\"data row5 col1\" >1226069403.2355</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row5_col2\" class=\"data row5 col2\" >35015.2739</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.6252</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row5_col4\" class=\"data row5 col4\" >1.1162</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row5_col5\" class=\"data row5 col5\" >1.9184</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row6_col0\" class=\"data row6 col0\" >24577.1693</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row6_col1\" class=\"data row6 col1\" >1067231342.2456</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row6_col2\" class=\"data row6 col2\" >32668.5069</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.6022</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row6_col4\" class=\"data row6 col4\" >1.8531</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row6_col5\" class=\"data row6 col5\" >1.9340</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row7_col0\" class=\"data row7 col0\" >25174.1766</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row7_col1\" class=\"data row7 col1\" >1485731641.1295</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row7_col2\" class=\"data row7 col2\" >38545.1896</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.5693</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row7_col4\" class=\"data row7 col4\" >1.5192</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row7_col5\" class=\"data row7 col5\" >12.0424</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row8_col0\" class=\"data row8 col0\" >18749.1517</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row8_col1\" class=\"data row8 col1\" >945214458.5499</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row8_col2\" class=\"data row8 col2\" >30744.3403</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.5953</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row8_col4\" class=\"data row8 col4\" >1.5579</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row8_col5\" class=\"data row8 col5\" >9.6187</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row9_col0\" class=\"data row9 col0\" >23819.5133</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row9_col1\" class=\"data row9 col1\" >970953833.1982</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row9_col2\" class=\"data row9 col2\" >31160.1321</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.4956</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.6420</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.6647</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col0\" class=\"data row10 col0\" >21606.9811</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col1\" class=\"data row10 col1\" >1137140854.3125</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col2\" class=\"data row10 col2\" >33213.6777</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.5895</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col4\" class=\"data row10 col4\" >1.4486</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row10_col5\" class=\"data row10 col5\" >6.7176</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >SD</th>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row11_col0\" class=\"data row11 col0\" >4478.6663</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row11_col1\" class=\"data row11 col1\" >368949630.3116</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row11_col2\" class=\"data row11 col2\" >5830.3058</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.1302</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.4053</td>\n",
              "                        <td id=\"T_17ee25ac_dfa2_11ea_ba03_0242ac1c0002row11_col5\" class=\"data row11 col5\" >6.0268</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f803d412438>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6gjtmrgjUGSE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "outputId": "08341a6b-443e-416e-90e4-73eaff11171e"
      },
      "source": [
        "predict_model(blend_specific);"
      ],
      "execution_count": 342,
      "outputs": [
        {
          "output_type": "display_data",
          "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>Model</th>\n",
              "      <th>MAE</th>\n",
              "      <th>MSE</th>\n",
              "      <th>RMSE</th>\n",
              "      <th>R2</th>\n",
              "      <th>RMSLE</th>\n",
              "      <th>MAPE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Voting Regressor</td>\n",
              "      <td>20091.1533</td>\n",
              "      <td>1.074017e+09</td>\n",
              "      <td>32772.2015</td>\n",
              "      <td>0.6294</td>\n",
              "      <td>1.4308</td>\n",
              "      <td>0    11.273639\n",
              "dtype: float64</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Model         MAE  ...   RMSLE                           MAPE\n",
              "0  Voting Regressor  20091.1533  ...  1.4308  0    11.273639\n",
              "dtype: float64\n",
              "\n",
              "[1 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fF1esVyJUExv",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "final_model = finalize_model(blend_specific)"
      ],
      "execution_count": 343,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "exxFJKhDUGBv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "bc61e04d-135a-4c49-d9a7-52bc47038227"
      },
      "source": [
        "unseen_predictions_2 = predict_model(final_model, data=test, round=0)\n",
        "unseen_predictions_2.loc[unseen_predictions_2['Label'] < 0, 'Label'] = 0\n",
        "unseen_predictions_2.head()"
      ],
      "execution_count": 344,
      "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>dayofweek</th>\n",
              "      <th>quarter</th>\n",
              "      <th>month</th>\n",
              "      <th>year</th>\n",
              "      <th>dayofyear</th>\n",
              "      <th>dayofmonth</th>\n",
              "      <th>weekofyear</th>\n",
              "      <th>flag</th>\n",
              "      <th>sale_dollars</th>\n",
              "      <th>Label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>168</td>\n",
              "      <td>16</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1376.22</td>\n",
              "      <td>5954.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>170</td>\n",
              "      <td>18</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>77424.58</td>\n",
              "      <td>55874.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>171</td>\n",
              "      <td>19</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>226.68</td>\n",
              "      <td>7973.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>174</td>\n",
              "      <td>22</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>97385.87</td>\n",
              "      <td>58838.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>2020</td>\n",
              "      <td>176</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>3810.90</td>\n",
              "      <td>6636.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   dayofweek  quarter  month  year  ...  weekofyear  flag  sale_dollars    Label\n",
              "0          1        2      6  2020  ...          25     1       1376.22   5954.0\n",
              "1          3        2      6  2020  ...          25     1      77424.58  55874.0\n",
              "2          4        2      6  2020  ...          25     1        226.68   7973.0\n",
              "3          0        2      6  2020  ...          26     1      97385.87  58838.0\n",
              "4          2        2      6  2020  ...          26     1       3810.90   6636.0\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 344
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BMYv_OMwUFhN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "outputId": "b7a79def-5529-4ae0-804e-71b45fc9c3f5"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "plot_series(test.index, test['sale_dollars'],\"True\")\n",
        "#plot_series(train['ds'],train['y'])\n",
        "#plot_series(X_test.index, unseen_predictions['Label'],'Prediction_1')\n",
        "plot_series(test.index, unseen_predictions_2['Label'],'Prediction_2')\n"
      ],
      "execution_count": 345,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NHslO6ficCto",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "stack_1 = stack_models([tuned_rf,tuned_xbb, tuned_lightgbm])\n",
        "predict_model(stack_1);\n",
        "final_stack_1 = finalize_model(stack_1)\n",
        "unseen_predictions_3 = predict_model(final_stack_1, data=test, round=0)\n"
      ],
      "execution_count": 346,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ofNoqfhAWlsj",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def calc_smape(y_hat, y):\n",
        "        return 100/len(y) * np.sum(2 * np.abs(y_hat - y) / (np.abs(y) + np.abs(y_hat)))"
      ],
      "execution_count": 347,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rTAbSUYbXmdx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "1fa180f9-aca9-45fb-f1e6-57d79a7e2fe4"
      },
      "source": [
        "calc_smape(test['sale_dollars'].values,unseen_predictions['Label'].values)"
      ],
      "execution_count": 348,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "77.5131395866915"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 348
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sru6fAMrWnSN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "a9880d8f-fa71-4747-dbeb-b8dce9a63b1d"
      },
      "source": [
        "calc_smape(test['sale_dollars'].values,unseen_predictions_2['Label'].values)"
      ],
      "execution_count": 349,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "67.11265129390662"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 349
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fX5cIpwrcjkh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "5ff51819-f033-4acc-ed70-80d973a634eb"
      },
      "source": [
        "calc_smape(test['sale_dollars'].values,unseen_predictions_3['Label'].values)"
      ],
      "execution_count": 350,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "130.17337377570843"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 350
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cnZDDXFkkxV6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}