Sales_Prediction_Using_Python.ipynb

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        "121ee2ab398747059ec47328590184c7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Navjotkhatri/OIBSIP/blob/main/Sales_Prediction_Using_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**TASK-5**\n",
        "# **Project Name- SALES PREDICTION USING PYTHON**\n",
        "**Contributor-Navjot Khatri**"
      ],
      "metadata": {
        "id": "gZDfGCFwXu3X"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Sales prediction means predicting how much of a product people will buy based on factors\n",
        "such as the amount you spend to advertise your product, the segment of people you\n",
        "advertise for, or the platform you are advertising on about your product.\n",
        "\n",
        "\n",
        "\n",
        "Typically, a product and service-based business always need their Data Scientist to predict\n",
        "their future sales with every step they take to manipulate the cost of advertising their\n",
        "product. So let’s start the task of sales prediction with machine learning using Python.\n",
        "\n"
      ],
      "metadata": {
        "id": "Ixgqxs6NYHIB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **pIP Install**"
      ],
      "metadata": {
        "id": "2EtTgqoT2uUl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#pip Package\n",
        "!pip install -q autoviz\n",
        "!pip install -q -U --pre pycaret"
      ],
      "metadata": {
        "id": "zHHnTncK-2L6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0ccf970e-732c-4e94-b2d5-a65c4a641bf7"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.7/64.7 KB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.9/12.9 MB\u001b[0m \u001b[31m34.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m74.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m120.9/120.9 KB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m83.6/83.6 KB\u001b[0m \u001b[31m10.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for emoji (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "cvxpy 1.3.1 requires setuptools>65.5.1, but you have setuptools 60.10.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m481.8/481.8 KB\u001b[0m \u001b[31m12.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m298.0/298.0 KB\u001b[0m \u001b[31m29.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m45.8/45.8 KB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[33m  WARNING: Requested plotly-resampler>=0.8.3.1 from https://files.pythonhosted.org/packages/d7/5e/71a9e34a36c1855d0c4e30a88405d58c4bbbe7ece802b188628a643f2cda/plotly_resampler-0.8.4rc1.tar.gz#sha256=154ebffa9778813fe457ac9112e71e085ac283644a1e26b869bd5c6b7bf064a2 (from pycaret), but installing version 0.8.4rc1\u001b[0m\u001b[33m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m212.2/212.2 KB\u001b[0m \u001b[31m21.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.2/10.2 MB\u001b[0m \u001b[31m55.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m101.5/101.5 KB\u001b[0m \u001b[31m12.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m101.1/101.1 KB\u001b[0m \u001b[31m12.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m95.6/95.6 KB\u001b[0m \u001b[31m13.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for plotly-resampler (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for pyod (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "pandas-profiling 3.2.0 requires joblib~=1.1.0, but you have joblib 1.2.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "* Pip is a package manager for Python that allows you to install additional libraries and packages that are not part of the standard Python library "
      ],
      "metadata": {
        "id": "4gv96wrq20Ut"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Import Library**"
      ],
      "metadata": {
        "id": "mpNC-nEj2VoD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#import library\n",
        "from ast import increment_lineno\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline"
      ],
      "metadata": {
        "id": "-EM12kxwiiaF"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Import Libarary for Machine Learning \n",
        "from scipy import stats\n",
        "from pandas_profiling import ProfileReport\n",
        "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
        "from autoviz.classify_method import data_cleaning_suggestions ,data_suggestions\n",
        "from pycaret.regression import *\n",
        "from pycaret  import regression\n",
        "from sklearn.model_selection import cross_val_score"
      ],
      "metadata": {
        "id": "Z3rRIOR0_KKM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#mount google drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "BNLVZq6J-qm3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "Mac56GKtXWxa"
      },
      "outputs": [],
      "source": [
        "#reading csv file\n",
        "working_dir_path=\"/content/drive/MyDrive/Colab Notebooks/Oasis Intern projects/Sales Prediction Using Python/Advertising.csv\"\n",
        "sales_df=pd.read_csv(working_dir_path)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Data Preprations**"
      ],
      "metadata": {
        "id": "Mn3NEBTn3noe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#first Five Row\n",
        "sales_df.head()"
      ],
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        "id": "5rF8PyDoiloL",
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          "height": 206
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      "execution_count": 6,
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              "   Unnamed: 0     TV  Radio  Newspaper  Sales\n",
              "0           1  230.1   37.8       69.2   22.1\n",
              "1           2   44.5   39.3       45.1   10.4\n",
              "2           3   17.2   45.9       69.3    9.3\n",
              "3           4  151.5   41.3       58.5   18.5\n",
              "4           5  180.8   10.8       58.4   12.9"
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              "      <th>4</th>\n",
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              "      <td>58.4</td>\n",
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      "source": [
        "#last Five Row\n",
        "sales_df.tail()"
      ],
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        "id": "Uu2kaBBNilyH",
        "colab": {
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          "height": 206
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      "execution_count": 7,
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              "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
              "195         196   38.2    3.7       13.8    7.6\n",
              "196         197   94.2    4.9        8.1    9.7\n",
              "197         198  177.0    9.3        6.4   12.8\n",
              "198         199  283.6   42.0       66.2   25.5\n",
              "199         200  232.1    8.6        8.7   13.4"
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              "      <th>195</th>\n",
              "      <td>196</td>\n",
              "      <td>38.2</td>\n",
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              "      <td>13.8</td>\n",
              "      <td>7.6</td>\n",
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              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>197</td>\n",
              "      <td>94.2</td>\n",
              "      <td>4.9</td>\n",
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              "      <td>198</td>\n",
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              "      <td>199</td>\n",
              "      <td>283.6</td>\n",
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              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>200</td>\n",
              "      <td>232.1</td>\n",
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              "\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
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          "metadata": {},
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      "cell_type": "code",
      "source": [
        "#Shape Of Our Dataset\n",
        "\n",
        "sales_df.shape"
      ],
      "metadata": {
        "id": "XhIj40OqSn89",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ade93874-b39c-4c11-9a26-7d9d7e0f7b37"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(200, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "#Statistical Information Of Data \n",
        "\n",
        "sales_df.info()"
      ],
      "metadata": {
        "id": "GE7rN50mil0v",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3d27663b-e70e-4920-bf80-52ffe8d15f18"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 200 entries, 0 to 199\n",
            "Data columns (total 5 columns):\n",
            " #   Column      Non-Null Count  Dtype  \n",
            "---  ------      --------------  -----  \n",
            " 0   Unnamed: 0  200 non-null    int64  \n",
            " 1   TV          200 non-null    float64\n",
            " 2   Radio       200 non-null    float64\n",
            " 3   Newspaper   200 non-null    float64\n",
            " 4   Sales       200 non-null    float64\n",
            "dtypes: float64(4), int64(1)\n",
            "memory usage: 7.9 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Descriptive Statistics Of our Dataset\n",
        "\n",
        "sales_df.describe()"
      ],
      "metadata": {
        "id": "jVEcNztMil3R",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
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        "outputId": "543b0ab8-d3d2-4a47-ab82-3b07c8947aa6"
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      "execution_count": 10,
      "outputs": [
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            "text/plain": [
              "       Unnamed: 0          TV       Radio   Newspaper       Sales\n",
              "count  200.000000  200.000000  200.000000  200.000000  200.000000\n",
              "mean   100.500000  147.042500   23.264000   30.554000   14.022500\n",
              "std     57.879185   85.854236   14.846809   21.778621    5.217457\n",
              "min      1.000000    0.700000    0.000000    0.300000    1.600000\n",
              "25%     50.750000   74.375000    9.975000   12.750000   10.375000\n",
              "50%    100.500000  149.750000   22.900000   25.750000   12.900000\n",
              "75%    150.250000  218.825000   36.525000   45.100000   17.400000\n",
              "max    200.000000  296.400000   49.600000  114.000000   27.000000"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>TV</th>\n",
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              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>200.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>100.500000</td>\n",
              "      <td>147.042500</td>\n",
              "      <td>23.264000</td>\n",
              "      <td>30.554000</td>\n",
              "      <td>14.022500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>57.879185</td>\n",
              "      <td>85.854236</td>\n",
              "      <td>14.846809</td>\n",
              "      <td>21.778621</td>\n",
              "      <td>5.217457</td>\n",
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              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.700000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>1.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>50.750000</td>\n",
              "      <td>74.375000</td>\n",
              "      <td>9.975000</td>\n",
              "      <td>12.750000</td>\n",
              "      <td>10.375000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>100.500000</td>\n",
              "      <td>149.750000</td>\n",
              "      <td>22.900000</td>\n",
              "      <td>25.750000</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>150.250000</td>\n",
              "      <td>218.825000</td>\n",
              "      <td>36.525000</td>\n",
              "      <td>45.100000</td>\n",
              "      <td>17.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>200.000000</td>\n",
              "      <td>296.400000</td>\n",
              "      <td>49.600000</td>\n",
              "      <td>114.000000</td>\n",
              "      <td>27.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-17f1ecba-5691-4b53-8b82-e2edbc85acf2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-17f1ecba-5691-4b53-8b82-e2edbc85acf2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ckeck Null Values if Any \n",
        "sales_df.isnull().sum()"
      ],
      "metadata": {
        "id": "-kXYH0Uuil5l",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1957d9e8-bfa8-4299-cafa-c638ed0d6913"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unnamed: 0    0\n",
              "TV            0\n",
              "Radio         0\n",
              "Newspaper     0\n",
              "Sales         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Drop unnecessary Column From DAta \n",
        "sales_df.drop('Unnamed: 0', axis = 1, inplace = True)"
      ],
      "metadata": {
        "id": "7Rkh3Kyzil8L"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sales_df.head()"
      ],
      "metadata": {
        "id": "AI9C2WzJil_m",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "854437b5-9779-4d65-9bcd-4480bcb56be0"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      TV  Radio  Newspaper  Sales\n",
              "0  230.1   37.8       69.2   22.1\n",
              "1   44.5   39.3       45.1   10.4\n",
              "2   17.2   45.9       69.3    9.3\n",
              "3  151.5   41.3       58.5   18.5\n",
              "4  180.8   10.8       58.4   12.9"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-302defbc-81ab-4aa1-8e32-80bcb56579ac\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>TV</th>\n",
              "      <th>Radio</th>\n",
              "      <th>Newspaper</th>\n",
              "      <th>Sales</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>230.1</td>\n",
              "      <td>37.8</td>\n",
              "      <td>69.2</td>\n",
              "      <td>22.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>44.5</td>\n",
              "      <td>39.3</td>\n",
              "      <td>45.1</td>\n",
              "      <td>10.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>17.2</td>\n",
              "      <td>45.9</td>\n",
              "      <td>69.3</td>\n",
              "      <td>9.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>151.5</td>\n",
              "      <td>41.3</td>\n",
              "      <td>58.5</td>\n",
              "      <td>18.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>180.8</td>\n",
              "      <td>10.8</td>\n",
              "      <td>58.4</td>\n",
              "      <td>12.9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-302defbc-81ab-4aa1-8e32-80bcb56579ac button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-302defbc-81ab-4aa1-8e32-80bcb56579ac');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Data visualisation**"
      ],
      "metadata": {
        "id": "omqVmkYV3u2z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#TV vs Sales Listing\n",
        "f = plt.figure()\n",
        "f.set_figwidth(20)\n",
        "f.set_figheight(10)\n",
        "plt.plot(sales_df[\"TV\"] ,label = \"TV\")\n",
        "plt.plot(sales_df[\"Sales\"] ,label = \"Sales\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "id": "DVCl1zzPtYPh",
        "outputId": "e1774dc4-2024-453c-a33e-4cc3fa9fd347"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Radio Vs sales Listing\n",
        "f = plt.figure()\n",
        "f.set_figwidth(20)\n",
        "f.set_figheight(10)\n",
        "plt.plot(sales_df[\"Radio\"] ,label = \"Radio\")\n",
        "plt.plot(sales_df[\"Sales\"] ,label = \"Sales\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "id": "DotLYcAoL5KT",
        "outputId": "7adf6009-f6d3-4042-c2d0-8e4efc192e34"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Newspaper vs Sales Listing\n",
        "f = plt.figure()\n",
        "f.set_figwidth(20)\n",
        "f.set_figheight(10)\n",
        "plt.plot(sales_df[\"Newspaper\"] ,label = \"Newspaper\")\n",
        "plt.plot(sales_df[\"Sales\"] ,label = \"Sales\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "id": "ClBbDVciMmS1",
        "outputId": "7f0fe53d-33b7-44f6-ec01-1fa9fa4d3289"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Data Cleanin Suggestions \n",
        "data_cleaning_suggestions(sales_df)"
      ],
      "metadata": {
        "id": "H5YaQKnB9Pcl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 192
        },
        "outputId": "1ca89942-a08b-47df-ff32-a5723ca9661f"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data cleaning improvement suggestions. Complete them before proceeding to ML modeling.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "text/html": [
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              "      <td id=\"T_eb3f2_row0_col3\" class=\"data row0 col3\" >0.000000</td>\n",
              "      <td id=\"T_eb3f2_row0_col4\" class=\"data row0 col4\" >95.000000</td>\n",
              "      <td id=\"T_eb3f2_row0_col5\" class=\"data row0 col5\" >0</td>\n",
              "      <td id=\"T_eb3f2_row0_col6\" class=\"data row0 col6\" ></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_eb3f2_level0_row1\" class=\"row_heading level0 row1\" >Newspaper</th>\n",
              "      <td id=\"T_eb3f2_row1_col0\" class=\"data row1 col0\" >172</td>\n",
              "      <td id=\"T_eb3f2_row1_col1\" class=\"data row1 col1\" >float64</td>\n",
              "      <td id=\"T_eb3f2_row1_col2\" class=\"data row1 col2\" >0</td>\n",
              "      <td id=\"T_eb3f2_row1_col3\" class=\"data row1 col3\" >0.000000</td>\n",
              "      <td id=\"T_eb3f2_row1_col4\" class=\"data row1 col4\" >86.000000</td>\n",
              "      <td id=\"T_eb3f2_row1_col5\" class=\"data row1 col5\" >0</td>\n",
              "      <td id=\"T_eb3f2_row1_col6\" class=\"data row1 col6\" ></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_eb3f2_level0_row2\" class=\"row_heading level0 row2\" >Radio</th>\n",
              "      <td id=\"T_eb3f2_row2_col0\" class=\"data row2 col0\" >167</td>\n",
              "      <td id=\"T_eb3f2_row2_col1\" class=\"data row2 col1\" >float64</td>\n",
              "      <td id=\"T_eb3f2_row2_col2\" class=\"data row2 col2\" >0</td>\n",
              "      <td id=\"T_eb3f2_row2_col3\" class=\"data row2 col3\" >0.000000</td>\n",
              "      <td id=\"T_eb3f2_row2_col4\" class=\"data row2 col4\" >83.500000</td>\n",
              "      <td id=\"T_eb3f2_row2_col5\" class=\"data row2 col5\" >0</td>\n",
              "      <td id=\"T_eb3f2_row2_col6\" class=\"data row2 col6\" ></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_eb3f2_level0_row3\" class=\"row_heading level0 row3\" >Sales</th>\n",
              "      <td id=\"T_eb3f2_row3_col0\" class=\"data row3 col0\" >121</td>\n",
              "      <td id=\"T_eb3f2_row3_col1\" class=\"data row3 col1\" >float64</td>\n",
              "      <td id=\"T_eb3f2_row3_col2\" class=\"data row3 col2\" >0</td>\n",
              "      <td id=\"T_eb3f2_row3_col3\" class=\"data row3 col3\" >0.000000</td>\n",
              "      <td id=\"T_eb3f2_row3_col4\" class=\"data row3 col4\" >60.500000</td>\n",
              "      <td id=\"T_eb3f2_row3_col5\" class=\"data row3 col5\" >0</td>\n",
              "      <td id=\"T_eb3f2_row3_col6\" class=\"data row3 col6\" ></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#correlation Graph\n",
        "plt.figure(figsize=(15,8))\n",
        "sns.heatmap(sales_df.corr(),annot=True)"
      ],
      "metadata": {
        "id": "bIq3w3wJ9VMF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "outputId": "a6cae72a-fd5d-4033-ee94-a13707efe381"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Detect OutLiers If Any**"
      ],
      "metadata": {
        "id": "bBjqmN5BGjEC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Define a function for detecting a outliers\n",
        "def detect_outliers(data):\n",
        "    outlier_percents = {}\n",
        "    for column in data.columns:\n",
        "        if data[column].dtype != object:\n",
        "            q1 = np.quantile(data[column], 0.25)\n",
        "            q3 = np.quantile(data[column], 0.75)\n",
        "            iqr = q3 - q1\n",
        "            upper_bound = q3 + (1.5 * iqr)\n",
        "            lower_bound = q1 - (1.5 * iqr)\n",
        "            outliers = data[(data[column] > upper_bound) | (data[column] < lower_bound)][column]\n",
        "            outlier_percentage = len(outliers) / len(data[column]) * 100\n",
        "            outlier_percents[column] = outlier_percentage\n",
        "            outlier_dataframe = pd.DataFrame(data = outlier_percents.values() ,index=outlier_percents.keys() ,columns=['Outlier_percentage'])\n",
        "    \n",
        "    return outlier_dataframe.sort_values(by = 'Outlier_percentage', ascending = False)"
      ],
      "metadata": {
        "id": "B2qEDDsQ_a9i"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Outlier_percentage\n",
        "detect_outliers(sales_df)"
      ],
      "metadata": {
        "id": "-i3bcLfv_a5-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "3ea4ab0f-117b-48c8-b2c5-b5c10644514b"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Outlier_percentage\n",
              "Newspaper                 1.0\n",
              "TV                        0.0\n",
              "Radio                     0.0\n",
              "Sales                     0.0"
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>Outlier_percentage</th>\n",
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              "      <th>Newspaper</th>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
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              "      <th>Sales</th>\n",
              "      <td>0.0</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e40ee0e5-c85c-4b22-bc42-e3e43b08c454')\"\n",
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              "\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e40ee0e5-c85c-4b22-bc42-e3e43b08c454 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e40ee0e5-c85c-4b22-bc42-e3e43b08c454');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = sales_df.drop('Sales', axis = 1)\n",
        "y = sales_df['Sales']"
      ],
      "metadata": {
        "id": "A-FgXd6a_a3v"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Transformed test set \n",
        "sl = setup(data = sales_df, target = 'Sales', session_id=123)"
      ],
      "metadata": {
        "id": "1L--B0pq_a1i",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "outputId": "4a6511ba-3709-4004-b895-ae46dc9bb96c"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fdb09d7b100>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_a5525_row8_col1 {\n",
              "  background-color: lightgreen;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_a5525\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_a5525_level0_col0\" class=\"col_heading level0 col0\" >Description</th>\n",
              "      <th id=\"T_a5525_level0_col1\" class=\"col_heading level0 col1\" >Value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_a5525_row0_col0\" class=\"data row0 col0\" >Session id</td>\n",
              "      <td id=\"T_a5525_row0_col1\" class=\"data row0 col1\" >123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_a5525_row1_col0\" class=\"data row1 col0\" >Target</td>\n",
              "      <td id=\"T_a5525_row1_col1\" class=\"data row1 col1\" >Sales</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_a5525_row2_col0\" class=\"data row2 col0\" >Target type</td>\n",
              "      <td id=\"T_a5525_row2_col1\" class=\"data row2 col1\" >Regression</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_a5525_row3_col0\" class=\"data row3 col0\" >Original data shape</td>\n",
              "      <td id=\"T_a5525_row3_col1\" class=\"data row3 col1\" >(200, 4)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_a5525_row4_col0\" class=\"data row4 col0\" >Transformed data shape</td>\n",
              "      <td id=\"T_a5525_row4_col1\" class=\"data row4 col1\" >(200, 4)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_a5525_row5_col0\" class=\"data row5 col0\" >Transformed train set shape</td>\n",
              "      <td id=\"T_a5525_row5_col1\" class=\"data row5 col1\" >(140, 4)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_a5525_row6_col0\" class=\"data row6 col0\" >Transformed test set shape</td>\n",
              "      <td id=\"T_a5525_row6_col1\" class=\"data row6 col1\" >(60, 4)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_a5525_row7_col0\" class=\"data row7 col0\" >Numeric features</td>\n",
              "      <td id=\"T_a5525_row7_col1\" class=\"data row7 col1\" >3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_a5525_row8_col0\" class=\"data row8 col0\" >Preprocess</td>\n",
              "      <td id=\"T_a5525_row8_col1\" class=\"data row8 col1\" >True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_a5525_row9_col0\" class=\"data row9 col0\" >Imputation type</td>\n",
              "      <td id=\"T_a5525_row9_col1\" class=\"data row9 col1\" >simple</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_a5525_row10_col0\" class=\"data row10 col0\" >Numeric imputation</td>\n",
              "      <td id=\"T_a5525_row10_col1\" class=\"data row10 col1\" >mean</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_a5525_row11_col0\" class=\"data row11 col0\" >Categorical imputation</td>\n",
              "      <td id=\"T_a5525_row11_col1\" class=\"data row11 col1\" >mode</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_a5525_row12_col0\" class=\"data row12 col0\" >Fold Generator</td>\n",
              "      <td id=\"T_a5525_row12_col1\" class=\"data row12 col1\" >KFold</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_a5525_row13_col0\" class=\"data row13 col0\" >Fold Number</td>\n",
              "      <td id=\"T_a5525_row13_col1\" class=\"data row13 col1\" >10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_a5525_row14_col0\" class=\"data row14 col0\" >CPU Jobs</td>\n",
              "      <td id=\"T_a5525_row14_col1\" class=\"data row14 col1\" >-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_a5525_row15_col0\" class=\"data row15 col0\" >Use GPU</td>\n",
              "      <td id=\"T_a5525_row15_col1\" class=\"data row15 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_a5525_row16_col0\" class=\"data row16 col0\" >Log Experiment</td>\n",
              "      <td id=\"T_a5525_row16_col1\" class=\"data row16 col1\" >False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_a5525_row17_col0\" class=\"data row17 col0\" >Experiment Name</td>\n",
              "      <td id=\"T_a5525_row17_col1\" class=\"data row17 col1\" >reg-default-name</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_a5525_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_a5525_row18_col0\" class=\"data row18 col0\" >USI</td>\n",
              "      <td id=\"T_a5525_row18_col1\" class=\"data row18 col1\" >cd97</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Extra Trees Regressor**"
      ],
      "metadata": {
        "id": "wMJ4l70_4KAT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Compare different Models\n",
        "compare_models()"
      ],
      "metadata": {
        "id": "ZKEAq-qU_azb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 702,
          "referenced_widgets": [
            "a1ddb11b296148d0bf2610c21a9ff3d8",
            "3fb9b4c7bc5a49f7ae0e06097decdb46",
            "ccc7dd571eb74995ae60d09df7907aa7",
            "69619402050040f087da4f0f483a9f49",
            "aace9d180d8f435cb9332145c501379a",
            "98a01522730e4603976abaa8cd785779",
            "7983f138de654894ae9c2ac22ba1a1c3",
            "a6a8a0ef2dce48b988a3418980db021d",
            "d43e5d4f8a7e4846b7e143323645adda",
            "a42b35eddf364aa4be269d8f9333179d",
            "acde102803ad4efdad9c15ea81d808e0"
          ]
        },
        "outputId": "80e720fd-9ebc-468f-dd5c-0f956590f871"
      },
      "execution_count": 23,
      "outputs": [
        {
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          "data": {
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              "  text-align: left;\n",
              "  background-color: yellow;\n",
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              "#T_c361e_row0_col7, #T_c361e_row1_col7, #T_c361e_row2_col7, #T_c361e_row3_col7, #T_c361e_row4_col7, #T_c361e_row5_col7, #T_c361e_row6_col7, #T_c361e_row7_col7, #T_c361e_row8_col7, #T_c361e_row9_col7, #T_c361e_row10_col7, #T_c361e_row11_col7, #T_c361e_row12_col7, #T_c361e_row13_col7, #T_c361e_row14_col7, #T_c361e_row15_col7, #T_c361e_row16_col7, #T_c361e_row18_col7 {\n",
              "  text-align: left;\n",
              "  background-color: lightgrey;\n",
              "}\n",
              "#T_c361e_row17_col7 {\n",
              "  text-align: left;\n",
              "  background-color: yellow;\n",
              "  background-color: lightgrey;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_c361e\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_c361e_level0_col0\" class=\"col_heading level0 col0\" >Model</th>\n",
              "      <th id=\"T_c361e_level0_col1\" class=\"col_heading level0 col1\" >MAE</th>\n",
              "      <th id=\"T_c361e_level0_col2\" class=\"col_heading level0 col2\" >MSE</th>\n",
              "      <th id=\"T_c361e_level0_col3\" class=\"col_heading level0 col3\" >RMSE</th>\n",
              "      <th id=\"T_c361e_level0_col4\" class=\"col_heading level0 col4\" >R2</th>\n",
              "      <th id=\"T_c361e_level0_col5\" class=\"col_heading level0 col5\" >RMSLE</th>\n",
              "      <th id=\"T_c361e_level0_col6\" class=\"col_heading level0 col6\" >MAPE</th>\n",
              "      <th id=\"T_c361e_level0_col7\" class=\"col_heading level0 col7\" >TT (Sec)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row0\" class=\"row_heading level0 row0\" >et</th>\n",
              "      <td id=\"T_c361e_row0_col0\" class=\"data row0 col0\" >Extra Trees Regressor</td>\n",
              "      <td id=\"T_c361e_row0_col1\" class=\"data row0 col1\" >0.4624</td>\n",
              "      <td id=\"T_c361e_row0_col2\" class=\"data row0 col2\" >0.4099</td>\n",
              "      <td id=\"T_c361e_row0_col3\" class=\"data row0 col3\" >0.6207</td>\n",
              "      <td id=\"T_c361e_row0_col4\" class=\"data row0 col4\" >0.9829</td>\n",
              "      <td id=\"T_c361e_row0_col5\" class=\"data row0 col5\" >0.0638</td>\n",
              "      <td id=\"T_c361e_row0_col6\" class=\"data row0 col6\" >0.0524</td>\n",
              "      <td id=\"T_c361e_row0_col7\" class=\"data row0 col7\" >0.5580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row1\" class=\"row_heading level0 row1\" >rf</th>\n",
              "      <td id=\"T_c361e_row1_col0\" class=\"data row1 col0\" >Random Forest Regressor</td>\n",
              "      <td id=\"T_c361e_row1_col1\" class=\"data row1 col1\" >0.6819</td>\n",
              "      <td id=\"T_c361e_row1_col2\" class=\"data row1 col2\" >0.7522</td>\n",
              "      <td id=\"T_c361e_row1_col3\" class=\"data row1 col3\" >0.8463</td>\n",
              "      <td id=\"T_c361e_row1_col4\" class=\"data row1 col4\" >0.9707</td>\n",
              "      <td id=\"T_c361e_row1_col5\" class=\"data row1 col5\" >0.0810</td>\n",
              "      <td id=\"T_c361e_row1_col6\" class=\"data row1 col6\" >0.0698</td>\n",
              "      <td id=\"T_c361e_row1_col7\" class=\"data row1 col7\" >0.4030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row2\" class=\"row_heading level0 row2\" >gbr</th>\n",
              "      <td id=\"T_c361e_row2_col0\" class=\"data row2 col0\" >Gradient Boosting Regressor</td>\n",
              "      <td id=\"T_c361e_row2_col1\" class=\"data row2 col1\" >0.6543</td>\n",
              "      <td id=\"T_c361e_row2_col2\" class=\"data row2 col2\" >0.7543</td>\n",
              "      <td id=\"T_c361e_row2_col3\" class=\"data row2 col3\" >0.8449</td>\n",
              "      <td id=\"T_c361e_row2_col4\" class=\"data row2 col4\" >0.9695</td>\n",
              "      <td id=\"T_c361e_row2_col5\" class=\"data row2 col5\" >0.0821</td>\n",
              "      <td id=\"T_c361e_row2_col6\" class=\"data row2 col6\" >0.0685</td>\n",
              "      <td id=\"T_c361e_row2_col7\" class=\"data row2 col7\" >0.3260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row3\" class=\"row_heading level0 row3\" >xgboost</th>\n",
              "      <td id=\"T_c361e_row3_col0\" class=\"data row3 col0\" >Extreme Gradient Boosting</td>\n",
              "      <td id=\"T_c361e_row3_col1\" class=\"data row3 col1\" >0.7092</td>\n",
              "      <td id=\"T_c361e_row3_col2\" class=\"data row3 col2\" >0.8571</td>\n",
              "      <td id=\"T_c361e_row3_col3\" class=\"data row3 col3\" >0.9083</td>\n",
              "      <td id=\"T_c361e_row3_col4\" class=\"data row3 col4\" >0.9628</td>\n",
              "      <td id=\"T_c361e_row3_col5\" class=\"data row3 col5\" >0.0842</td>\n",
              "      <td id=\"T_c361e_row3_col6\" class=\"data row3 col6\" >0.0708</td>\n",
              "      <td id=\"T_c361e_row3_col7\" class=\"data row3 col7\" >0.1280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row4\" class=\"row_heading level0 row4\" >ada</th>\n",
              "      <td id=\"T_c361e_row4_col0\" class=\"data row4 col0\" >AdaBoost Regressor</td>\n",
              "      <td id=\"T_c361e_row4_col1\" class=\"data row4 col1\" >0.9118</td>\n",
              "      <td id=\"T_c361e_row4_col2\" class=\"data row4 col2\" >1.3620</td>\n",
              "      <td id=\"T_c361e_row4_col3\" class=\"data row4 col3\" >1.1184</td>\n",
              "      <td id=\"T_c361e_row4_col4\" class=\"data row4 col4\" >0.9487</td>\n",
              "      <td id=\"T_c361e_row4_col5\" class=\"data row4 col5\" >0.1028</td>\n",
              "      <td id=\"T_c361e_row4_col6\" class=\"data row4 col6\" >0.0923</td>\n",
              "      <td id=\"T_c361e_row4_col7\" class=\"data row4 col7\" >0.4840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row5\" class=\"row_heading level0 row5\" >dt</th>\n",
              "      <td id=\"T_c361e_row5_col0\" class=\"data row5 col0\" >Decision Tree Regressor</td>\n",
              "      <td id=\"T_c361e_row5_col1\" class=\"data row5 col1\" >0.9336</td>\n",
              "      <td id=\"T_c361e_row5_col2\" class=\"data row5 col2\" >1.6092</td>\n",
              "      <td id=\"T_c361e_row5_col3\" class=\"data row5 col3\" >1.2321</td>\n",
              "      <td id=\"T_c361e_row5_col4\" class=\"data row5 col4\" >0.9283</td>\n",
              "      <td id=\"T_c361e_row5_col5\" class=\"data row5 col5\" >0.1167</td>\n",
              "      <td id=\"T_c361e_row5_col6\" class=\"data row5 col6\" >0.0949</td>\n",
              "      <td id=\"T_c361e_row5_col7\" class=\"data row5 col7\" >0.0530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row6\" class=\"row_heading level0 row6\" >lightgbm</th>\n",
              "      <td id=\"T_c361e_row6_col0\" class=\"data row6 col0\" >Light Gradient Boosting Machine</td>\n",
              "      <td id=\"T_c361e_row6_col1\" class=\"data row6 col1\" >0.9731</td>\n",
              "      <td id=\"T_c361e_row6_col2\" class=\"data row6 col2\" >1.8903</td>\n",
              "      <td id=\"T_c361e_row6_col3\" class=\"data row6 col3\" >1.3323</td>\n",
              "      <td id=\"T_c361e_row6_col4\" class=\"data row6 col4\" >0.9196</td>\n",
              "      <td id=\"T_c361e_row6_col5\" class=\"data row6 col5\" >0.1434</td>\n",
              "      <td id=\"T_c361e_row6_col6\" class=\"data row6 col6\" >0.1178</td>\n",
              "      <td id=\"T_c361e_row6_col7\" class=\"data row6 col7\" >0.1430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row7\" class=\"row_heading level0 row7\" >knn</th>\n",
              "      <td id=\"T_c361e_row7_col0\" class=\"data row7 col0\" >K Neighbors Regressor</td>\n",
              "      <td id=\"T_c361e_row7_col1\" class=\"data row7 col1\" >1.2407</td>\n",
              "      <td id=\"T_c361e_row7_col2\" class=\"data row7 col2\" >2.7481</td>\n",
              "      <td id=\"T_c361e_row7_col3\" class=\"data row7 col3\" >1.6193</td>\n",
              "      <td id=\"T_c361e_row7_col4\" class=\"data row7 col4\" >0.8813</td>\n",
              "      <td id=\"T_c361e_row7_col5\" class=\"data row7 col5\" >0.1221</td>\n",
              "      <td id=\"T_c361e_row7_col6\" class=\"data row7 col6\" >0.1120</td>\n",
              "      <td id=\"T_c361e_row7_col7\" class=\"data row7 col7\" >0.0780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row8\" class=\"row_heading level0 row8\" >llar</th>\n",
              "      <td id=\"T_c361e_row8_col0\" class=\"data row8 col0\" >Lasso Least Angle Regression</td>\n",
              "      <td id=\"T_c361e_row8_col1\" class=\"data row8 col1\" >1.3834</td>\n",
              "      <td id=\"T_c361e_row8_col2\" class=\"data row8 col2\" >3.3047</td>\n",
              "      <td id=\"T_c361e_row8_col3\" class=\"data row8 col3\" >1.7501</td>\n",
              "      <td id=\"T_c361e_row8_col4\" class=\"data row8 col4\" >0.8674</td>\n",
              "      <td id=\"T_c361e_row8_col5\" class=\"data row8 col5\" >0.1721</td>\n",
              "      <td id=\"T_c361e_row8_col6\" class=\"data row8 col6\" >0.1612</td>\n",
              "      <td id=\"T_c361e_row8_col7\" class=\"data row8 col7\" >0.0970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row9\" class=\"row_heading level0 row9\" >lasso</th>\n",
              "      <td id=\"T_c361e_row9_col0\" class=\"data row9 col0\" >Lasso Regression</td>\n",
              "      <td id=\"T_c361e_row9_col1\" class=\"data row9 col1\" >1.3834</td>\n",
              "      <td id=\"T_c361e_row9_col2\" class=\"data row9 col2\" >3.3047</td>\n",
              "      <td id=\"T_c361e_row9_col3\" class=\"data row9 col3\" >1.7500</td>\n",
              "      <td id=\"T_c361e_row9_col4\" class=\"data row9 col4\" >0.8674</td>\n",
              "      <td id=\"T_c361e_row9_col5\" class=\"data row9 col5\" >0.1721</td>\n",
              "      <td id=\"T_c361e_row9_col6\" class=\"data row9 col6\" >0.1612</td>\n",
              "      <td id=\"T_c361e_row9_col7\" class=\"data row9 col7\" >0.0820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row10\" class=\"row_heading level0 row10\" >en</th>\n",
              "      <td id=\"T_c361e_row10_col0\" class=\"data row10 col0\" >Elastic Net</td>\n",
              "      <td id=\"T_c361e_row10_col1\" class=\"data row10 col1\" >1.3842</td>\n",
              "      <td id=\"T_c361e_row10_col2\" class=\"data row10 col2\" >3.3202</td>\n",
              "      <td id=\"T_c361e_row10_col3\" class=\"data row10 col3\" >1.7524</td>\n",
              "      <td id=\"T_c361e_row10_col4\" class=\"data row10 col4\" >0.8669</td>\n",
              "      <td id=\"T_c361e_row10_col5\" class=\"data row10 col5\" >0.1734</td>\n",
              "      <td id=\"T_c361e_row10_col6\" class=\"data row10 col6\" >0.1621</td>\n",
              "      <td id=\"T_c361e_row10_col7\" class=\"data row10 col7\" >0.1040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row11\" class=\"row_heading level0 row11\" >lr</th>\n",
              "      <td id=\"T_c361e_row11_col0\" class=\"data row11 col0\" >Linear Regression</td>\n",
              "      <td id=\"T_c361e_row11_col1\" class=\"data row11 col1\" >1.3846</td>\n",
              "      <td id=\"T_c361e_row11_col2\" class=\"data row11 col2\" >3.3397</td>\n",
              "      <td id=\"T_c361e_row11_col3\" class=\"data row11 col3\" >1.7555</td>\n",
              "      <td id=\"T_c361e_row11_col4\" class=\"data row11 col4\" >0.8663</td>\n",
              "      <td id=\"T_c361e_row11_col5\" class=\"data row11 col5\" >0.1752</td>\n",
              "      <td id=\"T_c361e_row11_col6\" class=\"data row11 col6\" >0.1634</td>\n",
              "      <td id=\"T_c361e_row11_col7\" class=\"data row11 col7\" >0.8300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row12\" class=\"row_heading level0 row12\" >ridge</th>\n",
              "      <td id=\"T_c361e_row12_col0\" class=\"data row12 col0\" >Ridge Regression</td>\n",
              "      <td id=\"T_c361e_row12_col1\" class=\"data row12 col1\" >1.3846</td>\n",
              "      <td id=\"T_c361e_row12_col2\" class=\"data row12 col2\" >3.3397</td>\n",
              "      <td id=\"T_c361e_row12_col3\" class=\"data row12 col3\" >1.7555</td>\n",
              "      <td id=\"T_c361e_row12_col4\" class=\"data row12 col4\" >0.8663</td>\n",
              "      <td id=\"T_c361e_row12_col5\" class=\"data row12 col5\" >0.1752</td>\n",
              "      <td id=\"T_c361e_row12_col6\" class=\"data row12 col6\" >0.1634</td>\n",
              "      <td id=\"T_c361e_row12_col7\" class=\"data row12 col7\" >0.0610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row13\" class=\"row_heading level0 row13\" >lar</th>\n",
              "      <td id=\"T_c361e_row13_col0\" class=\"data row13 col0\" >Least Angle Regression</td>\n",
              "      <td id=\"T_c361e_row13_col1\" class=\"data row13 col1\" >1.3846</td>\n",
              "      <td id=\"T_c361e_row13_col2\" class=\"data row13 col2\" >3.3397</td>\n",
              "      <td id=\"T_c361e_row13_col3\" class=\"data row13 col3\" >1.7555</td>\n",
              "      <td id=\"T_c361e_row13_col4\" class=\"data row13 col4\" >0.8663</td>\n",
              "      <td id=\"T_c361e_row13_col5\" class=\"data row13 col5\" >0.1752</td>\n",
              "      <td id=\"T_c361e_row13_col6\" class=\"data row13 col6\" >0.1634</td>\n",
              "      <td id=\"T_c361e_row13_col7\" class=\"data row13 col7\" >0.0780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row14\" class=\"row_heading level0 row14\" >br</th>\n",
              "      <td id=\"T_c361e_row14_col0\" class=\"data row14 col0\" >Bayesian Ridge</td>\n",
              "      <td id=\"T_c361e_row14_col1\" class=\"data row14 col1\" >1.3888</td>\n",
              "      <td id=\"T_c361e_row14_col2\" class=\"data row14 col2\" >3.3451</td>\n",
              "      <td id=\"T_c361e_row14_col3\" class=\"data row14 col3\" >1.7580</td>\n",
              "      <td id=\"T_c361e_row14_col4\" class=\"data row14 col4\" >0.8659</td>\n",
              "      <td id=\"T_c361e_row14_col5\" class=\"data row14 col5\" >0.1743</td>\n",
              "      <td id=\"T_c361e_row14_col6\" class=\"data row14 col6\" >0.1631</td>\n",
              "      <td id=\"T_c361e_row14_col7\" class=\"data row14 col7\" >0.1020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row15\" class=\"row_heading level0 row15\" >huber</th>\n",
              "      <td id=\"T_c361e_row15_col0\" class=\"data row15 col0\" >Huber Regressor</td>\n",
              "      <td id=\"T_c361e_row15_col1\" class=\"data row15 col1\" >1.3405</td>\n",
              "      <td id=\"T_c361e_row15_col2\" class=\"data row15 col2\" >3.4828</td>\n",
              "      <td id=\"T_c361e_row15_col3\" class=\"data row15 col3\" >1.7876</td>\n",
              "      <td id=\"T_c361e_row15_col4\" class=\"data row15 col4\" >0.8618</td>\n",
              "      <td id=\"T_c361e_row15_col5\" class=\"data row15 col5\" >0.1780</td>\n",
              "      <td id=\"T_c361e_row15_col6\" class=\"data row15 col6\" >0.1661</td>\n",
              "      <td id=\"T_c361e_row15_col7\" class=\"data row15 col7\" >0.1180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row16\" class=\"row_heading level0 row16\" >omp</th>\n",
              "      <td id=\"T_c361e_row16_col0\" class=\"data row16 col0\" >Orthogonal Matching Pursuit</td>\n",
              "      <td id=\"T_c361e_row16_col1\" class=\"data row16 col1\" >2.6871</td>\n",
              "      <td id=\"T_c361e_row16_col2\" class=\"data row16 col2\" >11.2996</td>\n",
              "      <td id=\"T_c361e_row16_col3\" class=\"data row16 col3\" >3.3293</td>\n",
              "      <td id=\"T_c361e_row16_col4\" class=\"data row16 col4\" >0.4990</td>\n",
              "      <td id=\"T_c361e_row16_col5\" class=\"data row16 col5\" >0.2264</td>\n",
              "      <td id=\"T_c361e_row16_col6\" class=\"data row16 col6\" >0.2269</td>\n",
              "      <td id=\"T_c361e_row16_col7\" class=\"data row16 col7\" >0.1150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row17\" class=\"row_heading level0 row17\" >dummy</th>\n",
              "      <td id=\"T_c361e_row17_col0\" class=\"data row17 col0\" >Dummy Regressor</td>\n",
              "      <td id=\"T_c361e_row17_col1\" class=\"data row17 col1\" >4.3561</td>\n",
              "      <td id=\"T_c361e_row17_col2\" class=\"data row17 col2\" >27.7343</td>\n",
              "      <td id=\"T_c361e_row17_col3\" class=\"data row17 col3\" >5.1586</td>\n",
              "      <td id=\"T_c361e_row17_col4\" class=\"data row17 col4\" >-0.0588</td>\n",
              "      <td id=\"T_c361e_row17_col5\" class=\"data row17 col5\" >0.3803</td>\n",
              "      <td id=\"T_c361e_row17_col6\" class=\"data row17 col6\" >0.4259</td>\n",
              "      <td id=\"T_c361e_row17_col7\" class=\"data row17 col7\" >0.0400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_c361e_level0_row18\" class=\"row_heading level0 row18\" >par</th>\n",
              "      <td id=\"T_c361e_row18_col0\" class=\"data row18 col0\" >Passive Aggressive Regressor</td>\n",
              "      <td id=\"T_c361e_row18_col1\" class=\"data row18 col1\" >5.0575</td>\n",
              "      <td id=\"T_c361e_row18_col2\" class=\"data row18 col2\" >56.0901</td>\n",
              "      <td id=\"T_c361e_row18_col3\" class=\"data row18 col3\" >6.1967</td>\n",
              "      <td id=\"T_c361e_row18_col4\" class=\"data row18 col4\" >-1.0559</td>\n",
              "      <td id=\"T_c361e_row18_col5\" class=\"data row18 col5\" >0.3472</td>\n",
              "      <td id=\"T_c361e_row18_col6\" class=\"data row18 col6\" >0.3877</td>\n",
              "      <td id=\"T_c361e_row18_col7\" class=\"data row18 col7\" >0.0950</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
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              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ExtraTreesRegressor(n_jobs=-1, random_state=123)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ExtraTreesRegressor</label><div class=\"sk-toggleable__content\"><pre>ExtraTreesRegressor(n_jobs=-1, random_state=123)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Extra Trees Regressor Model Best Fit for This DataSet**\n",
        "\n",
        "                            MAE\tMSE\tRMSE\tR2\tRMSLE\tMAPE\tTT (Sec)\n",
        "\n",
        "et\tExtra Trees Regressor\t0.4624\t0.4099\t0.6207\t0.9829\t0.0638\t0.0524\t0.2390"
      ],
      "metadata": {
        "id": "jPdHDgxuhwwd"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Extra Trees Regressor Model**"
      ],
      "metadata": {
        "id": "571eGeXa-D5G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# create Extra Trees Regressor Model\n",
        "et = create_model('et')"
      ],
      "metadata": {
        "id": "1u07r5KV_axQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457,
          "referenced_widgets": [
            "d37bad717d244b15ac90e1dbee3b250a",
            "29cb9bf511f743339dafa3a06d3eeb99",
            "8925e967a4f943abb89edd385026201d",
            "2784443dfc244784a05a57456908e10e",
            "930a666ecf5b4349acc67e9b1b7eee1a",
            "c0c92ac7cd61459cb8ad87c3a9e71f83",
            "9541d64bd2e946ecbcdcb0849cb95770",
            "f0db05c5afdb45f0b280ea5a6a07e20b",
            "b30e3e4363c54201bd84ca61ef8cd7db",
            "7126ac10b1aa4e3bbf3970c1fc862fce",
            "121ee2ab398747059ec47328590184c7"
          ]
        },
        "outputId": "f72a3a5e-d28a-4cbe-94c9-96f0a73bdee1"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": []
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fdb11753430>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_746d5_row10_col0, #T_746d5_row10_col1, #T_746d5_row10_col2, #T_746d5_row10_col3, #T_746d5_row10_col4, #T_746d5_row10_col5 {\n",
              "  background: yellow;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_746d5\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_746d5_level0_col0\" class=\"col_heading level0 col0\" >MAE</th>\n",
              "      <th id=\"T_746d5_level0_col1\" class=\"col_heading level0 col1\" >MSE</th>\n",
              "      <th id=\"T_746d5_level0_col2\" class=\"col_heading level0 col2\" >RMSE</th>\n",
              "      <th id=\"T_746d5_level0_col3\" class=\"col_heading level0 col3\" >R2</th>\n",
              "      <th id=\"T_746d5_level0_col4\" class=\"col_heading level0 col4\" >RMSLE</th>\n",
              "      <th id=\"T_746d5_level0_col5\" class=\"col_heading level0 col5\" >MAPE</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th class=\"index_name level0\" >Fold</th>\n",
              "      <th class=\"blank col0\" >&nbsp;</th>\n",
              "      <th class=\"blank col1\" >&nbsp;</th>\n",
              "      <th class=\"blank col2\" >&nbsp;</th>\n",
              "      <th class=\"blank col3\" >&nbsp;</th>\n",
              "      <th class=\"blank col4\" >&nbsp;</th>\n",
              "      <th class=\"blank col5\" >&nbsp;</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_746d5_row0_col0\" class=\"data row0 col0\" >0.3637</td>\n",
              "      <td id=\"T_746d5_row0_col1\" class=\"data row0 col1\" >0.3478</td>\n",
              "      <td id=\"T_746d5_row0_col2\" class=\"data row0 col2\" >0.5897</td>\n",
              "      <td id=\"T_746d5_row0_col3\" class=\"data row0 col3\" >0.9842</td>\n",
              "      <td id=\"T_746d5_row0_col4\" class=\"data row0 col4\" >0.0373</td>\n",
              "      <td id=\"T_746d5_row0_col5\" class=\"data row0 col5\" >0.0286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_746d5_row1_col0\" class=\"data row1 col0\" >0.6276</td>\n",
              "      <td id=\"T_746d5_row1_col1\" class=\"data row1 col1\" >1.1538</td>\n",
              "      <td id=\"T_746d5_row1_col2\" class=\"data row1 col2\" >1.0741</td>\n",
              "      <td id=\"T_746d5_row1_col3\" class=\"data row1 col3\" >0.9629</td>\n",
              "      <td id=\"T_746d5_row1_col4\" class=\"data row1 col4\" >0.2399</td>\n",
              "      <td id=\"T_746d5_row1_col5\" class=\"data row1 col5\" >0.2001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_746d5_row2_col0\" class=\"data row2 col0\" >0.4551</td>\n",
              "      <td id=\"T_746d5_row2_col1\" class=\"data row2 col1\" >0.4245</td>\n",
              "      <td id=\"T_746d5_row2_col2\" class=\"data row2 col2\" >0.6515</td>\n",
              "      <td id=\"T_746d5_row2_col3\" class=\"data row2 col3\" >0.9864</td>\n",
              "      <td id=\"T_746d5_row2_col4\" class=\"data row2 col4\" >0.0389</td>\n",
              "      <td id=\"T_746d5_row2_col5\" class=\"data row2 col5\" >0.0328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_746d5_row3_col0\" class=\"data row3 col0\" >0.4281</td>\n",
              "      <td id=\"T_746d5_row3_col1\" class=\"data row3 col1\" >0.3163</td>\n",
              "      <td id=\"T_746d5_row3_col2\" class=\"data row3 col2\" >0.5624</td>\n",
              "      <td id=\"T_746d5_row3_col3\" class=\"data row3 col3\" >0.9733</td>\n",
              "      <td id=\"T_746d5_row3_col4\" class=\"data row3 col4\" >0.0404</td>\n",
              "      <td id=\"T_746d5_row3_col5\" class=\"data row3 col5\" >0.0326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_746d5_row4_col0\" class=\"data row4 col0\" >0.4111</td>\n",
              "      <td id=\"T_746d5_row4_col1\" class=\"data row4 col1\" >0.2964</td>\n",
              "      <td id=\"T_746d5_row4_col2\" class=\"data row4 col2\" >0.5444</td>\n",
              "      <td id=\"T_746d5_row4_col3\" class=\"data row4 col3\" >0.9760</td>\n",
              "      <td id=\"T_746d5_row4_col4\" class=\"data row4 col4\" >0.0422</td>\n",
              "      <td id=\"T_746d5_row4_col5\" class=\"data row4 col5\" >0.0323</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_746d5_row5_col0\" class=\"data row5 col0\" >0.4338</td>\n",
              "      <td id=\"T_746d5_row5_col1\" class=\"data row5 col1\" >0.2968</td>\n",
              "      <td id=\"T_746d5_row5_col2\" class=\"data row5 col2\" >0.5448</td>\n",
              "      <td id=\"T_746d5_row5_col3\" class=\"data row5 col3\" >0.9871</td>\n",
              "      <td id=\"T_746d5_row5_col4\" class=\"data row5 col4\" >0.0384</td>\n",
              "      <td id=\"T_746d5_row5_col5\" class=\"data row5 col5\" >0.0359</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_746d5_row6_col0\" class=\"data row6 col0\" >0.4693</td>\n",
              "      <td id=\"T_746d5_row6_col1\" class=\"data row6 col1\" >0.3032</td>\n",
              "      <td id=\"T_746d5_row6_col2\" class=\"data row6 col2\" >0.5506</td>\n",
              "      <td id=\"T_746d5_row6_col3\" class=\"data row6 col3\" >0.9909</td>\n",
              "      <td id=\"T_746d5_row6_col4\" class=\"data row6 col4\" >0.0468</td>\n",
              "      <td id=\"T_746d5_row6_col5\" class=\"data row6 col5\" >0.0407</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_746d5_row7_col0\" class=\"data row7 col0\" >0.4261</td>\n",
              "      <td id=\"T_746d5_row7_col1\" class=\"data row7 col1\" >0.2542</td>\n",
              "      <td id=\"T_746d5_row7_col2\" class=\"data row7 col2\" >0.5042</td>\n",
              "      <td id=\"T_746d5_row7_col3\" class=\"data row7 col3\" >0.9869</td>\n",
              "      <td id=\"T_746d5_row7_col4\" class=\"data row7 col4\" >0.0565</td>\n",
              "      <td id=\"T_746d5_row7_col5\" class=\"data row7 col5\" >0.0431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_746d5_row8_col0\" class=\"data row8 col0\" >0.4567</td>\n",
              "      <td id=\"T_746d5_row8_col1\" class=\"data row8 col1\" >0.3008</td>\n",
              "      <td id=\"T_746d5_row8_col2\" class=\"data row8 col2\" >0.5485</td>\n",
              "      <td id=\"T_746d5_row8_col3\" class=\"data row8 col3\" >0.9910</td>\n",
              "      <td id=\"T_746d5_row8_col4\" class=\"data row8 col4\" >0.0603</td>\n",
              "      <td id=\"T_746d5_row8_col5\" class=\"data row8 col5\" >0.0414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_746d5_row9_col0\" class=\"data row9 col0\" >0.5528</td>\n",
              "      <td id=\"T_746d5_row9_col1\" class=\"data row9 col1\" >0.4052</td>\n",
              "      <td id=\"T_746d5_row9_col2\" class=\"data row9 col2\" >0.6366</td>\n",
              "      <td id=\"T_746d5_row9_col3\" class=\"data row9 col3\" >0.9902</td>\n",
              "      <td id=\"T_746d5_row9_col4\" class=\"data row9 col4\" >0.0377</td>\n",
              "      <td id=\"T_746d5_row9_col5\" class=\"data row9 col5\" >0.0365</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row10\" class=\"row_heading level0 row10\" >Mean</th>\n",
              "      <td id=\"T_746d5_row10_col0\" class=\"data row10 col0\" >0.4624</td>\n",
              "      <td id=\"T_746d5_row10_col1\" class=\"data row10 col1\" >0.4099</td>\n",
              "      <td id=\"T_746d5_row10_col2\" class=\"data row10 col2\" >0.6207</td>\n",
              "      <td id=\"T_746d5_row10_col3\" class=\"data row10 col3\" >0.9829</td>\n",
              "      <td id=\"T_746d5_row10_col4\" class=\"data row10 col4\" >0.0638</td>\n",
              "      <td id=\"T_746d5_row10_col5\" class=\"data row10 col5\" >0.0524</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_746d5_level0_row11\" class=\"row_heading level0 row11\" >Std</th>\n",
              "      <td id=\"T_746d5_row11_col0\" class=\"data row11 col0\" >0.0716</td>\n",
              "      <td id=\"T_746d5_row11_col1\" class=\"data row11 col1\" >0.2529</td>\n",
              "      <td id=\"T_746d5_row11_col2\" class=\"data row11 col2\" >0.1570</td>\n",
              "      <td id=\"T_746d5_row11_col3\" class=\"data row11 col3\" >0.0088</td>\n",
              "      <td id=\"T_746d5_row11_col4\" class=\"data row11 col4\" >0.0592</td>\n",
              "      <td id=\"T_746d5_row11_col5\" class=\"data row11 col5\" >0.0494</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Processing:   0%|          | 0/4 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d37bad717d244b15ac90e1dbee3b250a"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/b3e629b1971e1542/manager.min.js"
                }
              }
            }
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": []
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "et = finalize_model(et)\n",
        "et"
      ],
      "metadata": {
        "id": "1auhwZWF_avK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 290
        },
        "outputId": "288a79ef-a3a3-4c27-9cec-79d5b7f3d5e9"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pipeline(memory=FastMemory(location=/tmp/joblib),\n",
              "         steps=[('numerical_imputer',\n",
              "                 TransformerWrapper(include=['TV', 'Radio', 'Newspaper'],\n",
              "                                    transformer=SimpleImputer())),\n",
              "                ('categorical_imputer',\n",
              "                 TransformerWrapper(include=[],\n",
              "                                    transformer=SimpleImputer(strategy='most_frequent'))),\n",
              "                ('actual_estimator',\n",
              "                 ExtraTreesRegressor(n_jobs=-1, random_state=123))])"
            ],
            "text/html": [
              "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(memory=FastMemory(location=/tmp/joblib),\n",
              "         steps=[(&#x27;numerical_imputer&#x27;,\n",
              "                 TransformerWrapper(include=[&#x27;TV&#x27;, &#x27;Radio&#x27;, &#x27;Newspaper&#x27;],\n",
              "                                    transformer=SimpleImputer())),\n",
              "                (&#x27;categorical_imputer&#x27;,\n",
              "                 TransformerWrapper(include=[],\n",
              "                                    transformer=SimpleImputer(strategy=&#x27;most_frequent&#x27;))),\n",
              "                (&#x27;actual_estimator&#x27;,\n",
              "                 ExtraTreesRegressor(n_jobs=-1, random_state=123))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(memory=FastMemory(location=/tmp/joblib),\n",
              "         steps=[(&#x27;numerical_imputer&#x27;,\n",
              "                 TransformerWrapper(include=[&#x27;TV&#x27;, &#x27;Radio&#x27;, &#x27;Newspaper&#x27;],\n",
              "                                    transformer=SimpleImputer())),\n",
              "                (&#x27;categorical_imputer&#x27;,\n",
              "                 TransformerWrapper(include=[],\n",
              "                                    transformer=SimpleImputer(strategy=&#x27;most_frequent&#x27;))),\n",
              "                (&#x27;actual_estimator&#x27;,\n",
              "                 ExtraTreesRegressor(n_jobs=-1, random_state=123))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">numerical_imputer: TransformerWrapper</label><div class=\"sk-toggleable__content\"><pre>TransformerWrapper(include=[&#x27;TV&#x27;, &#x27;Radio&#x27;, &#x27;Newspaper&#x27;],\n",
              "                   transformer=SimpleImputer())</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">transformer: SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer()</pre></div></div></div></div></div></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">categorical_imputer: TransformerWrapper</label><div class=\"sk-toggleable__content\"><pre>TransformerWrapper(include=[],\n",
              "                   transformer=SimpleImputer(strategy=&#x27;most_frequent&#x27;))</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">transformer: SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer(strategy=&#x27;most_frequent&#x27;)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SimpleImputer</label><div class=\"sk-toggleable__content\"><pre>SimpleImputer(strategy=&#x27;most_frequent&#x27;)</pre></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ExtraTreesRegressor</label><div class=\"sk-toggleable__content\"><pre>ExtraTreesRegressor(n_jobs=-1, random_state=123)</pre></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Prediction**"
      ],
      "metadata": {
        "id": "MxEGoKmLGUBj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Model Prediction\n",
        "preds = predict_model(et)"
      ],
      "metadata": {
        "id": "B3mb3deq_ast",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "outputId": "a6ae9686-4fcb-47cd-fa3d-a6a0b7a522b4"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7fdb70511d90>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "</style>\n",
              "<table id=\"T_4e268\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_4e268_level0_col0\" class=\"col_heading level0 col0\" >Model</th>\n",
              "      <th id=\"T_4e268_level0_col1\" class=\"col_heading level0 col1\" >MAE</th>\n",
              "      <th id=\"T_4e268_level0_col2\" class=\"col_heading level0 col2\" >MSE</th>\n",
              "      <th id=\"T_4e268_level0_col3\" class=\"col_heading level0 col3\" >RMSE</th>\n",
              "      <th id=\"T_4e268_level0_col4\" class=\"col_heading level0 col4\" >R2</th>\n",
              "      <th id=\"T_4e268_level0_col5\" class=\"col_heading level0 col5\" >RMSLE</th>\n",
              "      <th id=\"T_4e268_level0_col6\" class=\"col_heading level0 col6\" >MAPE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_4e268_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_4e268_row0_col0\" class=\"data row0 col0\" >Extra Trees Regressor</td>\n",
              "      <td id=\"T_4e268_row0_col1\" class=\"data row0 col1\" >0.0000</td>\n",
              "      <td id=\"T_4e268_row0_col2\" class=\"data row0 col2\" >0.0000</td>\n",
              "      <td id=\"T_4e268_row0_col3\" class=\"data row0 col3\" >0.0000</td>\n",
              "      <td id=\"T_4e268_row0_col4\" class=\"data row0 col4\" >1.0000</td>\n",
              "      <td id=\"T_4e268_row0_col5\" class=\"data row0 col5\" >0.0000</td>\n",
              "      <td id=\"T_4e268_row0_col6\" class=\"data row0 col6\" >0.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**R2 Score : 1.00**"
      ],
      "metadata": {
        "id": "3CWMoWEZFnAK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#predicted Values\n",
        "preds"
      ],
      "metadata": {
        "id": "M3yjjegM_aqe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "aa2de21a-3d86-41e8-bbe3-9eebf75f3d57"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             TV      Radio  Newspaper      Sales  prediction_label\n",
              "50   199.800003   3.100000  34.599998  11.400000         11.400000\n",
              "127   80.199997   0.000000   9.200000   8.800000          8.800000\n",
              "37    74.699997  49.400002  45.700001  14.700000         14.700000\n",
              "149   44.700001  25.799999  20.600000  10.100000         10.100000\n",
              "19   147.300003  23.900000  19.100000  14.600000         14.600000\n",
              "104  238.199997  34.299999   5.300000  20.700001         20.700001\n",
              "179  165.600006  10.000000  17.600000  12.600000         12.600000\n",
              "53   182.600006  46.200001  58.700001  21.200001         21.200001\n",
              "162  188.399994  18.100000  25.600000  14.900000         14.900000\n",
              "158   11.700000  36.900002  45.200001   7.300000          7.300000\n",
              "82    75.300003  20.299999  32.500000  11.300000         11.300000\n",
              "185  205.000000  45.099998  19.600000  22.600000         22.600000\n",
              "182   56.200001   5.700000  29.700001   8.700000          8.700000\n",
              "189   18.700001  12.100000  23.400000   6.700000          6.700000\n",
              "108   13.100000   0.400000  25.600000   5.300000          5.300000\n",
              "31   112.900002  17.400000  38.599998  11.900000         11.900000\n",
              "4    180.800003  10.800000  58.400002  12.900000         12.900000\n",
              "178  276.700012   2.300000  23.700001  11.800000         11.800000\n",
              "121   18.799999  21.700001  50.400002   7.000000          7.000000\n",
              "20   218.399994  27.700001  53.400002  18.000000         18.000000\n",
              "172   19.600000  20.100000  17.000000   7.600000          7.600000\n",
              "88    88.300003  25.500000  73.400002  12.900000         12.900000\n",
              "166   17.900000  37.599998  21.600000   8.000000          8.000000\n",
              "170   50.000000  11.600000  18.400000   8.400000          8.400000\n",
              "128  220.300003  49.000000   3.200000  24.700001         24.700001\n",
              "72    26.799999  33.000000  19.299999   8.800000          8.800000\n",
              "180  156.600006   2.600000   8.300000  10.500000         10.500000\n",
              "26   142.899994  29.299999  12.600000  15.000000         15.000000\n",
              "144   96.199997  14.800000  38.900002  11.400000         11.400000\n",
              "52   216.399994  41.700001  39.599998  22.600000         22.600000\n",
              "79   116.000000   7.700000  23.100000  11.000000         11.000000\n",
              "93   250.899994  36.500000  72.300003  22.200001         22.200001\n",
              "183  287.600006  43.000000  71.800003  26.200001         26.200001\n",
              "119   19.400000  16.000000  22.299999   6.600000          6.600000\n",
              "85   193.199997  18.400000  65.699997  15.200000         15.200000\n",
              "133  219.800003  33.500000  45.099998  19.600000         19.600000\n",
              "184  253.800003  21.299999  30.000000  17.600000         17.600000\n",
              "139  184.899994  43.900002   1.700000  20.700001         20.700001\n",
              "95   163.300003  31.600000  52.900002  16.900000         16.900000\n",
              "140   73.400002  17.000000  12.900000  10.900000         10.900000\n",
              "24    62.299999  12.600000  18.299999   9.700000          9.700000\n",
              "150  280.700012  13.900000  37.000000  16.100000         16.100000\n",
              "114   78.199997  46.799999  34.500000  14.600000         14.600000\n",
              "33   265.600006  20.000000   0.300000  17.400000         17.400000\n",
              "23   228.300003  16.900000  26.200001  15.500000         15.500000\n",
              "171  164.500000  20.900000  47.400002  14.500000         14.500000\n",
              "41   177.000000  33.400002  38.700001  17.100000         17.100000\n",
              "100  222.399994   4.300000  49.799999  11.700000         11.700000\n",
              "152  197.600006  23.299999  14.200000  16.600000         16.600000\n",
              "71   109.800003  14.300000  31.700001  12.400000         12.400000\n",
              "186  139.500000   2.100000  26.600000  10.300000         10.300000\n",
              "110  225.800003   8.200000  56.500000  13.400000         13.400000\n",
              "42   293.600006  27.700001   1.800000  20.700001         20.700001\n",
              "120  141.300003  26.799999  46.200001  15.500000         15.500000\n",
              "191   75.500000  10.800000   6.000000   9.900000          9.900000\n",
              "161   85.699997  35.799999  49.299999  13.300000         13.300000\n",
              "10    66.099998   5.800000  24.200001   8.600000          8.600000\n",
              "175  276.899994  48.900002  41.799999  27.000000         27.000000\n",
              "77   120.500000  28.500000  14.200000  14.200000         14.200000\n",
              "62   239.300003  15.500000  27.299999  15.700000         15.700000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5bb1b0b1-968a-433e-92d1-bef975110ceb\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>TV</th>\n",
              "      <th>Radio</th>\n",
              "      <th>Newspaper</th>\n",
              "      <th>Sales</th>\n",
              "      <th>prediction_label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>199.800003</td>\n",
              "      <td>3.100000</td>\n",
              "      <td>34.599998</td>\n",
              "      <td>11.400000</td>\n",
              "      <td>11.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>80.199997</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9.200000</td>\n",
              "      <td>8.800000</td>\n",
              "      <td>8.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>74.699997</td>\n",
              "      <td>49.400002</td>\n",
              "      <td>45.700001</td>\n",
              "      <td>14.700000</td>\n",
              "      <td>14.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>44.700001</td>\n",
              "      <td>25.799999</td>\n",
              "      <td>20.600000</td>\n",
              "      <td>10.100000</td>\n",
              "      <td>10.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>147.300003</td>\n",
              "      <td>23.900000</td>\n",
              "      <td>19.100000</td>\n",
              "      <td>14.600000</td>\n",
              "      <td>14.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>238.199997</td>\n",
              "      <td>34.299999</td>\n",
              "      <td>5.300000</td>\n",
              "      <td>20.700001</td>\n",
              "      <td>20.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>179</th>\n",
              "      <td>165.600006</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>17.600000</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>12.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>182.600006</td>\n",
              "      <td>46.200001</td>\n",
              "      <td>58.700001</td>\n",
              "      <td>21.200001</td>\n",
              "      <td>21.200001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>188.399994</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>25.600000</td>\n",
              "      <td>14.900000</td>\n",
              "      <td>14.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>11.700000</td>\n",
              "      <td>36.900002</td>\n",
              "      <td>45.200001</td>\n",
              "      <td>7.300000</td>\n",
              "      <td>7.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>75.300003</td>\n",
              "      <td>20.299999</td>\n",
              "      <td>32.500000</td>\n",
              "      <td>11.300000</td>\n",
              "      <td>11.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>185</th>\n",
              "      <td>205.000000</td>\n",
              "      <td>45.099998</td>\n",
              "      <td>19.600000</td>\n",
              "      <td>22.600000</td>\n",
              "      <td>22.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>182</th>\n",
              "      <td>56.200001</td>\n",
              "      <td>5.700000</td>\n",
              "      <td>29.700001</td>\n",
              "      <td>8.700000</td>\n",
              "      <td>8.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>18.700001</td>\n",
              "      <td>12.100000</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>6.700000</td>\n",
              "      <td>6.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>13.100000</td>\n",
              "      <td>0.400000</td>\n",
              "      <td>25.600000</td>\n",
              "      <td>5.300000</td>\n",
              "      <td>5.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>112.900002</td>\n",
              "      <td>17.400000</td>\n",
              "      <td>38.599998</td>\n",
              "      <td>11.900000</td>\n",
              "      <td>11.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>180.800003</td>\n",
              "      <td>10.800000</td>\n",
              "      <td>58.400002</td>\n",
              "      <td>12.900000</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>178</th>\n",
              "      <td>276.700012</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>23.700001</td>\n",
              "      <td>11.800000</td>\n",
              "      <td>11.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>18.799999</td>\n",
              "      <td>21.700001</td>\n",
              "      <td>50.400002</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>7.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>218.399994</td>\n",
              "      <td>27.700001</td>\n",
              "      <td>53.400002</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>18.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>172</th>\n",
              "      <td>19.600000</td>\n",
              "      <td>20.100000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>7.600000</td>\n",
              "      <td>7.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>88.300003</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>73.400002</td>\n",
              "      <td>12.900000</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>166</th>\n",
              "      <td>17.900000</td>\n",
              "      <td>37.599998</td>\n",
              "      <td>21.600000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>11.600000</td>\n",
              "      <td>18.400000</td>\n",
              "      <td>8.400000</td>\n",
              "      <td>8.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>220.300003</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>3.200000</td>\n",
              "      <td>24.700001</td>\n",
              "      <td>24.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>26.799999</td>\n",
              "      <td>33.000000</td>\n",
              "      <td>19.299999</td>\n",
              "      <td>8.800000</td>\n",
              "      <td>8.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>180</th>\n",
              "      <td>156.600006</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>8.300000</td>\n",
              "      <td>10.500000</td>\n",
              "      <td>10.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>142.899994</td>\n",
              "      <td>29.299999</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>15.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>144</th>\n",
              "      <td>96.199997</td>\n",
              "      <td>14.800000</td>\n",
              "      <td>38.900002</td>\n",
              "      <td>11.400000</td>\n",
              "      <td>11.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>216.399994</td>\n",
              "      <td>41.700001</td>\n",
              "      <td>39.599998</td>\n",
              "      <td>22.600000</td>\n",
              "      <td>22.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>116.000000</td>\n",
              "      <td>7.700000</td>\n",
              "      <td>23.100000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>11.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>93</th>\n",
              "      <td>250.899994</td>\n",
              "      <td>36.500000</td>\n",
              "      <td>72.300003</td>\n",
              "      <td>22.200001</td>\n",
              "      <td>22.200001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183</th>\n",
              "      <td>287.600006</td>\n",
              "      <td>43.000000</td>\n",
              "      <td>71.800003</td>\n",
              "      <td>26.200001</td>\n",
              "      <td>26.200001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>19.400000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>22.299999</td>\n",
              "      <td>6.600000</td>\n",
              "      <td>6.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>193.199997</td>\n",
              "      <td>18.400000</td>\n",
              "      <td>65.699997</td>\n",
              "      <td>15.200000</td>\n",
              "      <td>15.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>133</th>\n",
              "      <td>219.800003</td>\n",
              "      <td>33.500000</td>\n",
              "      <td>45.099998</td>\n",
              "      <td>19.600000</td>\n",
              "      <td>19.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>184</th>\n",
              "      <td>253.800003</td>\n",
              "      <td>21.299999</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>17.600000</td>\n",
              "      <td>17.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>184.899994</td>\n",
              "      <td>43.900002</td>\n",
              "      <td>1.700000</td>\n",
              "      <td>20.700001</td>\n",
              "      <td>20.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>163.300003</td>\n",
              "      <td>31.600000</td>\n",
              "      <td>52.900002</td>\n",
              "      <td>16.900000</td>\n",
              "      <td>16.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>73.400002</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>12.900000</td>\n",
              "      <td>10.900000</td>\n",
              "      <td>10.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>62.299999</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>18.299999</td>\n",
              "      <td>9.700000</td>\n",
              "      <td>9.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>150</th>\n",
              "      <td>280.700012</td>\n",
              "      <td>13.900000</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>16.100000</td>\n",
              "      <td>16.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>78.199997</td>\n",
              "      <td>46.799999</td>\n",
              "      <td>34.500000</td>\n",
              "      <td>14.600000</td>\n",
              "      <td>14.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>265.600006</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>17.400000</td>\n",
              "      <td>17.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>228.300003</td>\n",
              "      <td>16.900000</td>\n",
              "      <td>26.200001</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>15.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>171</th>\n",
              "      <td>164.500000</td>\n",
              "      <td>20.900000</td>\n",
              "      <td>47.400002</td>\n",
              "      <td>14.500000</td>\n",
              "      <td>14.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>177.000000</td>\n",
              "      <td>33.400002</td>\n",
              "      <td>38.700001</td>\n",
              "      <td>17.100000</td>\n",
              "      <td>17.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>222.399994</td>\n",
              "      <td>4.300000</td>\n",
              "      <td>49.799999</td>\n",
              "      <td>11.700000</td>\n",
              "      <td>11.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>152</th>\n",
              "      <td>197.600006</td>\n",
              "      <td>23.299999</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>16.600000</td>\n",
              "      <td>16.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>109.800003</td>\n",
              "      <td>14.300000</td>\n",
              "      <td>31.700001</td>\n",
              "      <td>12.400000</td>\n",
              "      <td>12.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>139.500000</td>\n",
              "      <td>2.100000</td>\n",
              "      <td>26.600000</td>\n",
              "      <td>10.300000</td>\n",
              "      <td>10.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>225.800003</td>\n",
              "      <td>8.200000</td>\n",
              "      <td>56.500000</td>\n",
              "      <td>13.400000</td>\n",
              "      <td>13.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>293.600006</td>\n",
              "      <td>27.700001</td>\n",
              "      <td>1.800000</td>\n",
              "      <td>20.700001</td>\n",
              "      <td>20.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>141.300003</td>\n",
              "      <td>26.799999</td>\n",
              "      <td>46.200001</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>15.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>75.500000</td>\n",
              "      <td>10.800000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>9.900000</td>\n",
              "      <td>9.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>85.699997</td>\n",
              "      <td>35.799999</td>\n",
              "      <td>49.299999</td>\n",
              "      <td>13.300000</td>\n",
              "      <td>13.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>66.099998</td>\n",
              "      <td>5.800000</td>\n",
              "      <td>24.200001</td>\n",
              "      <td>8.600000</td>\n",
              "      <td>8.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>175</th>\n",
              "      <td>276.899994</td>\n",
              "      <td>48.900002</td>\n",
              "      <td>41.799999</td>\n",
              "      <td>27.000000</td>\n",
              "      <td>27.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>77</th>\n",
              "      <td>120.500000</td>\n",
              "      <td>28.500000</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>14.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>239.300003</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>27.299999</td>\n",
              "      <td>15.700000</td>\n",
              "      <td>15.700000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sales_prediction=preds"
      ],
      "metadata": {
        "id": "cabJhnpcBL0R"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sales_prediction.head()"
      ],
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        "outputId": "34eeaa8c-a7c6-469c-9879-569403ed43cd"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             TV      Radio  Newspaper  Sales  prediction_label\n",
              "50   199.800003   3.100000  34.599998   11.4              11.4\n",
              "127   80.199997   0.000000   9.200000    8.8               8.8\n",
              "37    74.699997  49.400002  45.700001   14.7              14.7\n",
              "149   44.700001  25.799999  20.600000   10.1              10.1\n",
              "19   147.300003  23.900000  19.100000   14.6              14.6"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>TV</th>\n",
              "      <th>Radio</th>\n",
              "      <th>Newspaper</th>\n",
              "      <th>Sales</th>\n",
              "      <th>prediction_label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>199.800003</td>\n",
              "      <td>3.100000</td>\n",
              "      <td>34.599998</td>\n",
              "      <td>11.4</td>\n",
              "      <td>11.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>80.199997</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9.200000</td>\n",
              "      <td>8.8</td>\n",
              "      <td>8.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>74.699997</td>\n",
              "      <td>49.400002</td>\n",
              "      <td>45.700001</td>\n",
              "      <td>14.7</td>\n",
              "      <td>14.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>44.700001</td>\n",
              "      <td>25.799999</td>\n",
              "      <td>20.600000</td>\n",
              "      <td>10.1</td>\n",
              "      <td>10.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>147.300003</td>\n",
              "      <td>23.900000</td>\n",
              "      <td>19.100000</td>\n",
              "      <td>14.6</td>\n",
              "      <td>14.6</td>\n",
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          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sales_prediction= sales_prediction.rename(columns={'prediction_label': 'Sales_Prediction'}).reset_index()"
      ],
      "metadata": {
        "id": "hVxFjZCXBfSU"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sales_prediction"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "2VDCjQUoCH9Q",
        "outputId": "02f1322c-11c3-43be-a98c-0d69d3eda7b9"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    index          TV      Radio  Newspaper      Sales  Sales_Prediction\n",
              "0      50  199.800003   3.100000  34.599998  11.400000         11.400000\n",
              "1     127   80.199997   0.000000   9.200000   8.800000          8.800000\n",
              "2      37   74.699997  49.400002  45.700001  14.700000         14.700000\n",
              "3     149   44.700001  25.799999  20.600000  10.100000         10.100000\n",
              "4      19  147.300003  23.900000  19.100000  14.600000         14.600000\n",
              "5     104  238.199997  34.299999   5.300000  20.700001         20.700001\n",
              "6     179  165.600006  10.000000  17.600000  12.600000         12.600000\n",
              "7      53  182.600006  46.200001  58.700001  21.200001         21.200001\n",
              "8     162  188.399994  18.100000  25.600000  14.900000         14.900000\n",
              "9     158   11.700000  36.900002  45.200001   7.300000          7.300000\n",
              "10     82   75.300003  20.299999  32.500000  11.300000         11.300000\n",
              "11    185  205.000000  45.099998  19.600000  22.600000         22.600000\n",
              "12    182   56.200001   5.700000  29.700001   8.700000          8.700000\n",
              "13    189   18.700001  12.100000  23.400000   6.700000          6.700000\n",
              "14    108   13.100000   0.400000  25.600000   5.300000          5.300000\n",
              "15     31  112.900002  17.400000  38.599998  11.900000         11.900000\n",
              "16      4  180.800003  10.800000  58.400002  12.900000         12.900000\n",
              "17    178  276.700012   2.300000  23.700001  11.800000         11.800000\n",
              "18    121   18.799999  21.700001  50.400002   7.000000          7.000000\n",
              "19     20  218.399994  27.700001  53.400002  18.000000         18.000000\n",
              "20    172   19.600000  20.100000  17.000000   7.600000          7.600000\n",
              "21     88   88.300003  25.500000  73.400002  12.900000         12.900000\n",
              "22    166   17.900000  37.599998  21.600000   8.000000          8.000000\n",
              "23    170   50.000000  11.600000  18.400000   8.400000          8.400000\n",
              "24    128  220.300003  49.000000   3.200000  24.700001         24.700001\n",
              "25     72   26.799999  33.000000  19.299999   8.800000          8.800000\n",
              "26    180  156.600006   2.600000   8.300000  10.500000         10.500000\n",
              "27     26  142.899994  29.299999  12.600000  15.000000         15.000000\n",
              "28    144   96.199997  14.800000  38.900002  11.400000         11.400000\n",
              "29     52  216.399994  41.700001  39.599998  22.600000         22.600000\n",
              "30     79  116.000000   7.700000  23.100000  11.000000         11.000000\n",
              "31     93  250.899994  36.500000  72.300003  22.200001         22.200001\n",
              "32    183  287.600006  43.000000  71.800003  26.200001         26.200001\n",
              "33    119   19.400000  16.000000  22.299999   6.600000          6.600000\n",
              "34     85  193.199997  18.400000  65.699997  15.200000         15.200000\n",
              "35    133  219.800003  33.500000  45.099998  19.600000         19.600000\n",
              "36    184  253.800003  21.299999  30.000000  17.600000         17.600000\n",
              "37    139  184.899994  43.900002   1.700000  20.700001         20.700001\n",
              "38     95  163.300003  31.600000  52.900002  16.900000         16.900000\n",
              "39    140   73.400002  17.000000  12.900000  10.900000         10.900000\n",
              "40     24   62.299999  12.600000  18.299999   9.700000          9.700000\n",
              "41    150  280.700012  13.900000  37.000000  16.100000         16.100000\n",
              "42    114   78.199997  46.799999  34.500000  14.600000         14.600000\n",
              "43     33  265.600006  20.000000   0.300000  17.400000         17.400000\n",
              "44     23  228.300003  16.900000  26.200001  15.500000         15.500000\n",
              "45    171  164.500000  20.900000  47.400002  14.500000         14.500000\n",
              "46     41  177.000000  33.400002  38.700001  17.100000         17.100000\n",
              "47    100  222.399994   4.300000  49.799999  11.700000         11.700000\n",
              "48    152  197.600006  23.299999  14.200000  16.600000         16.600000\n",
              "49     71  109.800003  14.300000  31.700001  12.400000         12.400000\n",
              "50    186  139.500000   2.100000  26.600000  10.300000         10.300000\n",
              "51    110  225.800003   8.200000  56.500000  13.400000         13.400000\n",
              "52     42  293.600006  27.700001   1.800000  20.700001         20.700001\n",
              "53    120  141.300003  26.799999  46.200001  15.500000         15.500000\n",
              "54    191   75.500000  10.800000   6.000000   9.900000          9.900000\n",
              "55    161   85.699997  35.799999  49.299999  13.300000         13.300000\n",
              "56     10   66.099998   5.800000  24.200001   8.600000          8.600000\n",
              "57    175  276.899994  48.900002  41.799999  27.000000         27.000000\n",
              "58     77  120.500000  28.500000  14.200000  14.200000         14.200000\n",
              "59     62  239.300003  15.500000  27.299999  15.700000         15.700000"
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>TV</th>\n",
              "      <th>Radio</th>\n",
              "      <th>Newspaper</th>\n",
              "      <th>Sales</th>\n",
              "      <th>Sales_Prediction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>50</td>\n",
              "      <td>199.800003</td>\n",
              "      <td>3.100000</td>\n",
              "      <td>34.599998</td>\n",
              "      <td>11.400000</td>\n",
              "      <td>11.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>127</td>\n",
              "      <td>80.199997</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9.200000</td>\n",
              "      <td>8.800000</td>\n",
              "      <td>8.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>37</td>\n",
              "      <td>74.699997</td>\n",
              "      <td>49.400002</td>\n",
              "      <td>45.700001</td>\n",
              "      <td>14.700000</td>\n",
              "      <td>14.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>149</td>\n",
              "      <td>44.700001</td>\n",
              "      <td>25.799999</td>\n",
              "      <td>20.600000</td>\n",
              "      <td>10.100000</td>\n",
              "      <td>10.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>19</td>\n",
              "      <td>147.300003</td>\n",
              "      <td>23.900000</td>\n",
              "      <td>19.100000</td>\n",
              "      <td>14.600000</td>\n",
              "      <td>14.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>104</td>\n",
              "      <td>238.199997</td>\n",
              "      <td>34.299999</td>\n",
              "      <td>5.300000</td>\n",
              "      <td>20.700001</td>\n",
              "      <td>20.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>179</td>\n",
              "      <td>165.600006</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>17.600000</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>12.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>53</td>\n",
              "      <td>182.600006</td>\n",
              "      <td>46.200001</td>\n",
              "      <td>58.700001</td>\n",
              "      <td>21.200001</td>\n",
              "      <td>21.200001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>162</td>\n",
              "      <td>188.399994</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>25.600000</td>\n",
              "      <td>14.900000</td>\n",
              "      <td>14.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>158</td>\n",
              "      <td>11.700000</td>\n",
              "      <td>36.900002</td>\n",
              "      <td>45.200001</td>\n",
              "      <td>7.300000</td>\n",
              "      <td>7.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>82</td>\n",
              "      <td>75.300003</td>\n",
              "      <td>20.299999</td>\n",
              "      <td>32.500000</td>\n",
              "      <td>11.300000</td>\n",
              "      <td>11.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>185</td>\n",
              "      <td>205.000000</td>\n",
              "      <td>45.099998</td>\n",
              "      <td>19.600000</td>\n",
              "      <td>22.600000</td>\n",
              "      <td>22.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>182</td>\n",
              "      <td>56.200001</td>\n",
              "      <td>5.700000</td>\n",
              "      <td>29.700001</td>\n",
              "      <td>8.700000</td>\n",
              "      <td>8.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>189</td>\n",
              "      <td>18.700001</td>\n",
              "      <td>12.100000</td>\n",
              "      <td>23.400000</td>\n",
              "      <td>6.700000</td>\n",
              "      <td>6.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>108</td>\n",
              "      <td>13.100000</td>\n",
              "      <td>0.400000</td>\n",
              "      <td>25.600000</td>\n",
              "      <td>5.300000</td>\n",
              "      <td>5.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>31</td>\n",
              "      <td>112.900002</td>\n",
              "      <td>17.400000</td>\n",
              "      <td>38.599998</td>\n",
              "      <td>11.900000</td>\n",
              "      <td>11.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>4</td>\n",
              "      <td>180.800003</td>\n",
              "      <td>10.800000</td>\n",
              "      <td>58.400002</td>\n",
              "      <td>12.900000</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>178</td>\n",
              "      <td>276.700012</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>23.700001</td>\n",
              "      <td>11.800000</td>\n",
              "      <td>11.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>121</td>\n",
              "      <td>18.799999</td>\n",
              "      <td>21.700001</td>\n",
              "      <td>50.400002</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>7.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>20</td>\n",
              "      <td>218.399994</td>\n",
              "      <td>27.700001</td>\n",
              "      <td>53.400002</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>18.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>172</td>\n",
              "      <td>19.600000</td>\n",
              "      <td>20.100000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>7.600000</td>\n",
              "      <td>7.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>88</td>\n",
              "      <td>88.300003</td>\n",
              "      <td>25.500000</td>\n",
              "      <td>73.400002</td>\n",
              "      <td>12.900000</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>166</td>\n",
              "      <td>17.900000</td>\n",
              "      <td>37.599998</td>\n",
              "      <td>21.600000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>170</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>11.600000</td>\n",
              "      <td>18.400000</td>\n",
              "      <td>8.400000</td>\n",
              "      <td>8.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>128</td>\n",
              "      <td>220.300003</td>\n",
              "      <td>49.000000</td>\n",
              "      <td>3.200000</td>\n",
              "      <td>24.700001</td>\n",
              "      <td>24.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>72</td>\n",
              "      <td>26.799999</td>\n",
              "      <td>33.000000</td>\n",
              "      <td>19.299999</td>\n",
              "      <td>8.800000</td>\n",
              "      <td>8.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>180</td>\n",
              "      <td>156.600006</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>8.300000</td>\n",
              "      <td>10.500000</td>\n",
              "      <td>10.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>26</td>\n",
              "      <td>142.899994</td>\n",
              "      <td>29.299999</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>15.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>144</td>\n",
              "      <td>96.199997</td>\n",
              "      <td>14.800000</td>\n",
              "      <td>38.900002</td>\n",
              "      <td>11.400000</td>\n",
              "      <td>11.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>52</td>\n",
              "      <td>216.399994</td>\n",
              "      <td>41.700001</td>\n",
              "      <td>39.599998</td>\n",
              "      <td>22.600000</td>\n",
              "      <td>22.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>79</td>\n",
              "      <td>116.000000</td>\n",
              "      <td>7.700000</td>\n",
              "      <td>23.100000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>11.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>93</td>\n",
              "      <td>250.899994</td>\n",
              "      <td>36.500000</td>\n",
              "      <td>72.300003</td>\n",
              "      <td>22.200001</td>\n",
              "      <td>22.200001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>183</td>\n",
              "      <td>287.600006</td>\n",
              "      <td>43.000000</td>\n",
              "      <td>71.800003</td>\n",
              "      <td>26.200001</td>\n",
              "      <td>26.200001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>119</td>\n",
              "      <td>19.400000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>22.299999</td>\n",
              "      <td>6.600000</td>\n",
              "      <td>6.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>85</td>\n",
              "      <td>193.199997</td>\n",
              "      <td>18.400000</td>\n",
              "      <td>65.699997</td>\n",
              "      <td>15.200000</td>\n",
              "      <td>15.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>133</td>\n",
              "      <td>219.800003</td>\n",
              "      <td>33.500000</td>\n",
              "      <td>45.099998</td>\n",
              "      <td>19.600000</td>\n",
              "      <td>19.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>184</td>\n",
              "      <td>253.800003</td>\n",
              "      <td>21.299999</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>17.600000</td>\n",
              "      <td>17.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>139</td>\n",
              "      <td>184.899994</td>\n",
              "      <td>43.900002</td>\n",
              "      <td>1.700000</td>\n",
              "      <td>20.700001</td>\n",
              "      <td>20.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>95</td>\n",
              "      <td>163.300003</td>\n",
              "      <td>31.600000</td>\n",
              "      <td>52.900002</td>\n",
              "      <td>16.900000</td>\n",
              "      <td>16.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>140</td>\n",
              "      <td>73.400002</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>12.900000</td>\n",
              "      <td>10.900000</td>\n",
              "      <td>10.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>24</td>\n",
              "      <td>62.299999</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>18.299999</td>\n",
              "      <td>9.700000</td>\n",
              "      <td>9.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>150</td>\n",
              "      <td>280.700012</td>\n",
              "      <td>13.900000</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>16.100000</td>\n",
              "      <td>16.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>114</td>\n",
              "      <td>78.199997</td>\n",
              "      <td>46.799999</td>\n",
              "      <td>34.500000</td>\n",
              "      <td>14.600000</td>\n",
              "      <td>14.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>33</td>\n",
              "      <td>265.600006</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>17.400000</td>\n",
              "      <td>17.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>23</td>\n",
              "      <td>228.300003</td>\n",
              "      <td>16.900000</td>\n",
              "      <td>26.200001</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>15.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>171</td>\n",
              "      <td>164.500000</td>\n",
              "      <td>20.900000</td>\n",
              "      <td>47.400002</td>\n",
              "      <td>14.500000</td>\n",
              "      <td>14.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>41</td>\n",
              "      <td>177.000000</td>\n",
              "      <td>33.400002</td>\n",
              "      <td>38.700001</td>\n",
              "      <td>17.100000</td>\n",
              "      <td>17.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>100</td>\n",
              "      <td>222.399994</td>\n",
              "      <td>4.300000</td>\n",
              "      <td>49.799999</td>\n",
              "      <td>11.700000</td>\n",
              "      <td>11.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>152</td>\n",
              "      <td>197.600006</td>\n",
              "      <td>23.299999</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>16.600000</td>\n",
              "      <td>16.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>71</td>\n",
              "      <td>109.800003</td>\n",
              "      <td>14.300000</td>\n",
              "      <td>31.700001</td>\n",
              "      <td>12.400000</td>\n",
              "      <td>12.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>186</td>\n",
              "      <td>139.500000</td>\n",
              "      <td>2.100000</td>\n",
              "      <td>26.600000</td>\n",
              "      <td>10.300000</td>\n",
              "      <td>10.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>110</td>\n",
              "      <td>225.800003</td>\n",
              "      <td>8.200000</td>\n",
              "      <td>56.500000</td>\n",
              "      <td>13.400000</td>\n",
              "      <td>13.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>42</td>\n",
              "      <td>293.600006</td>\n",
              "      <td>27.700001</td>\n",
              "      <td>1.800000</td>\n",
              "      <td>20.700001</td>\n",
              "      <td>20.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>120</td>\n",
              "      <td>141.300003</td>\n",
              "      <td>26.799999</td>\n",
              "      <td>46.200001</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>15.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>191</td>\n",
              "      <td>75.500000</td>\n",
              "      <td>10.800000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>9.900000</td>\n",
              "      <td>9.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>161</td>\n",
              "      <td>85.699997</td>\n",
              "      <td>35.799999</td>\n",
              "      <td>49.299999</td>\n",
              "      <td>13.300000</td>\n",
              "      <td>13.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>10</td>\n",
              "      <td>66.099998</td>\n",
              "      <td>5.800000</td>\n",
              "      <td>24.200001</td>\n",
              "      <td>8.600000</td>\n",
              "      <td>8.600000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>175</td>\n",
              "      <td>276.899994</td>\n",
              "      <td>48.900002</td>\n",
              "      <td>41.799999</td>\n",
              "      <td>27.000000</td>\n",
              "      <td>27.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>77</td>\n",
              "      <td>120.500000</td>\n",
              "      <td>28.500000</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>14.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>62</td>\n",
              "      <td>239.300003</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>27.299999</td>\n",
              "      <td>15.700000</td>\n",
              "      <td>15.700000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Extra Trees Regressor Model**\n",
        "\n",
        "Extra Trees Regressor is an ensemble machine learning algorithm that is used for regression tasks. It is based on the Random Forest algorithm and works by creating a large number of decision trees, each using a random subset of the available features and data. It then combines the predictions of all these decision trees to make a final prediction. One key difference between Extra Trees and Random Forest is that Extra Trees selects the splitting thresholds of each node randomly, rather than searching for the best threshold. This makes Extra Trees faster to train than Random Forests, while still achieving good predictive performance."
      ],
      "metadata": {
        "id": "WtA7XHjqE5O4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**R^2 Score**\n",
        "\n",
        "R2 is a measure of the goodness of fit of a model. In regression, the R2 coefficient of determination is a statistical measure of how well the regression predictions approximate the real data points. An R2 of 1 indicates that the regression predictions perfectly fit the data."
      ],
      "metadata": {
        "id": "1GgXYGzRF9Fg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Thank You**\n",
        "          \n",
        "          -Navjot Khatri"
      ],
      "metadata": {
        "id": "uQ3L3o0HEp8U"
      }
    }
  ]
}