Car_Price_Prediction_assignment_solved_updated.ipynb

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    "colab": {
      "name": "Car Price Prediction assignment solved.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bJUV8yz2h9no"
      },
      "source": [
        "# Car Price Prediction::"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Stt2JW1Kh9nr"
      },
      "source": [
        "Download dataset from this link:\n",
        "\n",
        "https://www.kaggle.com/hellbuoy/car-price-prediction"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VPbPLvIzh9ns"
      },
      "source": [
        "# Problem Statement::"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uD_7M_8oh9ns"
      },
      "source": [
        "A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.\n",
        "\n",
        "They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the American market, since those may be very different from the Chinese market. The company wants to know:\n",
        "\n",
        "Which variables are significant in predicting the price of a car\n",
        "How well those variables describe the price of a car\n",
        "Based on various market surveys, the consulting firm has gathered a large data set of different types of cars across the America market.\n",
        "\n",
        "# task::\n",
        "We are required to model the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "INKwd3Xth9nt"
      },
      "source": [
        "# WORKFLOW ::"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4vdsT1_bh9nu"
      },
      "source": [
        "1.Load Data\n",
        "\n",
        "2.Check Missing Values ( If Exist ; Fill each record with mean of its feature )\n",
        "\n",
        "3.Split into 50% Training(Samples,Labels) , 30% Test(Samples,Labels) and 20% Validation Data(Samples,Labels).\n",
        "\n",
        "4.Model : input Layer (No. of features ), 3 hidden layers including 10,8,6 unit & Output Layer with activation function relu/tanh (check by experiment).\n",
        "\n",
        "5.Compilation Step (Note : Its a Regression problem , select loss , metrics according to it)\n",
        "6.Train the Model with Epochs (100) and validate it\n",
        "\n",
        "7.If the model gets overfit tune your model by changing the units , No. of layers , activation function , epochs , add dropout layer or add Regularizer according to the need .\n",
        "\n",
        "8.Evaluation Step\n",
        "\n",
        "9.Prediction"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n1e0mO7fRjVx"
      },
      "source": [
        "## **Loading Data**\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 140
        },
        "id": "R0COO7KWh9nw",
        "outputId": "3613d914-ce2f-4c21-ba6c-3db7ab4b7b50"
      },
      "source": [
        "from google.colab import files \n",
        "\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-154ecfd4-e082-404b-8753-698d90625f21\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-154ecfd4-e082-404b-8753-698d90625f21\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving CarPrice_Assignment.csv to CarPrice_Assignment.csv\n",
            "Saving Data Dictionary - carprices.xlsx to Data Dictionary - carprices.xlsx\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DYxsdbd5h9nx"
      },
      "source": [
        "import pandas as pd\n",
        "dataframe = pd.read_csv('CarPrice_Assignment.csv')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QHAS03-OSASZ"
      },
      "source": [
        "## **Checking for Missing Values**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B5gc-MDuyKTV",
        "outputId": "3a446d1f-9f75-4067-9fda-e29fb28ba7d8"
      },
      "source": [
        "dataframe.isnull().sum()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "car_ID              0\n",
              "symboling           0\n",
              "CarName             0\n",
              "fueltype            0\n",
              "aspiration          0\n",
              "doornumber          0\n",
              "carbody             0\n",
              "drivewheel          0\n",
              "enginelocation      0\n",
              "wheelbase           0\n",
              "carlength           0\n",
              "carwidth            0\n",
              "carheight           0\n",
              "curbweight          0\n",
              "enginetype          0\n",
              "cylindernumber      0\n",
              "enginesize          0\n",
              "fuelsystem          0\n",
              "boreratio           0\n",
              "stroke              0\n",
              "compressionratio    0\n",
              "horsepower          0\n",
              "peakrpm             0\n",
              "citympg             0\n",
              "highwaympg          0\n",
              "price               0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y5jupx4XyveX",
        "outputId": "1a8c1840-6e33-498a-9bab-31ad1ae90900"
      },
      "source": [
        "dataframe.isnull().any().any()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uFXSn_ub5sG8",
        "outputId": "e5524051-af5c-4561-d5bd-4f48bfba2828"
      },
      "source": [
        "xlsx = pd.ExcelFile('Data Dictionary - carprices.xlsx')\n",
        "\n",
        "data_dict = pd.read_excel(xlsx)\n",
        "data_dict.notnull().sum()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unnamed: 0      0\n",
              "Unnamed: 1      0\n",
              "Unnamed: 2      0\n",
              "Unnamed: 3      0\n",
              "Unnamed: 4      0\n",
              "Unnamed: 5      0\n",
              "Unnamed: 6     27\n",
              "Unnamed: 7     26\n",
              "Unnamed: 8      0\n",
              "Unnamed: 9      0\n",
              "Unnamed: 10     0\n",
              "Unnamed: 11    26\n",
              "Unnamed: 12     0\n",
              "Unnamed: 13     1\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7IXcnfwo6omW"
      },
      "source": [
        "data_dict.dropna(axis = 1, how = 'any', inplace = True, thresh = 20)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "id": "er8kvPtiK6tl",
        "outputId": "f7fc0cb7-4498-4005-9292-91f26f440310"
      },
      "source": [
        "data_dict[:10]"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Unnamed: 6</th>\n",
              "      <th>Unnamed: 7</th>\n",
              "      <th>Unnamed: 11</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>DATA DICTONARY</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>Car_ID</td>\n",
              "      <td>Unique id of each observation (Interger)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>Symboling</td>\n",
              "      <td>Its assigned insurance risk rating, A value of...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>3</td>\n",
              "      <td>carCompany</td>\n",
              "      <td>Name of car company (Categorical)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>4</td>\n",
              "      <td>fueltype</td>\n",
              "      <td>Car fuel type i.e gas or diesel (Categorical)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>5</td>\n",
              "      <td>aspiration</td>\n",
              "      <td>Aspiration used in a car (Categorical)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>6</td>\n",
              "      <td>doornumber</td>\n",
              "      <td>Number of doors in a car (Categorical)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>7</td>\n",
              "      <td>carbody</td>\n",
              "      <td>body of car (Categorical)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Unnamed: 6  ...                                        Unnamed: 11\n",
              "0             NaN  ...                                                NaN\n",
              "1  DATA DICTONARY  ...                                                NaN\n",
              "2             NaN  ...                                                NaN\n",
              "3               1  ...           Unique id of each observation (Interger)\n",
              "4               2  ...  Its assigned insurance risk rating, A value of...\n",
              "5               3  ...                  Name of car company (Categorical)\n",
              "6               4  ...      Car fuel type i.e gas or diesel (Categorical)\n",
              "7               5  ...             Aspiration used in a car (Categorical)\n",
              "8               6  ...             Number of doors in a car (Categorical)\n",
              "9               7  ...                          body of car (Categorical)\n",
              "\n",
              "[10 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iOqxNImmh9nx",
        "outputId": "36def035-3fa9-423e-84e0-e9fa9d4da7ce"
      },
      "source": [
        "dataframe.shape"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(205, 26)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 872
        },
        "id": "JHgeNcoH23MN",
        "outputId": "067057b3-3d08-4c16-8ad6-f417197c5f45"
      },
      "source": [
        "dataframe.head().T"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>car_ID</th>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>symboling</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CarName</th>\n",
              "      <td>alfa-romero giulia</td>\n",
              "      <td>alfa-romero stelvio</td>\n",
              "      <td>alfa-romero Quadrifoglio</td>\n",
              "      <td>audi 100 ls</td>\n",
              "      <td>audi 100ls</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fueltype</th>\n",
              "      <td>gas</td>\n",
              "      <td>gas</td>\n",
              "      <td>gas</td>\n",
              "      <td>gas</td>\n",
              "      <td>gas</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>aspiration</th>\n",
              "      <td>std</td>\n",
              "      <td>std</td>\n",
              "      <td>std</td>\n",
              "      <td>std</td>\n",
              "      <td>std</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>doornumber</th>\n",
              "      <td>two</td>\n",
              "      <td>two</td>\n",
              "      <td>two</td>\n",
              "      <td>four</td>\n",
              "      <td>four</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>carbody</th>\n",
              "      <td>convertible</td>\n",
              "      <td>convertible</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>sedan</td>\n",
              "      <td>sedan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>drivewheel</th>\n",
              "      <td>rwd</td>\n",
              "      <td>rwd</td>\n",
              "      <td>rwd</td>\n",
              "      <td>fwd</td>\n",
              "      <td>4wd</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>enginelocation</th>\n",
              "      <td>front</td>\n",
              "      <td>front</td>\n",
              "      <td>front</td>\n",
              "      <td>front</td>\n",
              "      <td>front</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>wheelbase</th>\n",
              "      <td>88.6</td>\n",
              "      <td>88.6</td>\n",
              "      <td>94.5</td>\n",
              "      <td>99.8</td>\n",
              "      <td>99.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>carlength</th>\n",
              "      <td>168.8</td>\n",
              "      <td>168.8</td>\n",
              "      <td>171.2</td>\n",
              "      <td>176.6</td>\n",
              "      <td>176.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>carwidth</th>\n",
              "      <td>64.1</td>\n",
              "      <td>64.1</td>\n",
              "      <td>65.5</td>\n",
              "      <td>66.2</td>\n",
              "      <td>66.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>carheight</th>\n",
              "      <td>48.8</td>\n",
              "      <td>48.8</td>\n",
              "      <td>52.4</td>\n",
              "      <td>54.3</td>\n",
              "      <td>54.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>curbweight</th>\n",
              "      <td>2548</td>\n",
              "      <td>2548</td>\n",
              "      <td>2823</td>\n",
              "      <td>2337</td>\n",
              "      <td>2824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>enginetype</th>\n",
              "      <td>dohc</td>\n",
              "      <td>dohc</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>ohc</td>\n",
              "      <td>ohc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cylindernumber</th>\n",
              "      <td>four</td>\n",
              "      <td>four</td>\n",
              "      <td>six</td>\n",
              "      <td>four</td>\n",
              "      <td>five</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>enginesize</th>\n",
              "      <td>130</td>\n",
              "      <td>130</td>\n",
              "      <td>152</td>\n",
              "      <td>109</td>\n",
              "      <td>136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fuelsystem</th>\n",
              "      <td>mpfi</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>mpfi</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>boreratio</th>\n",
              "      <td>3.47</td>\n",
              "      <td>3.47</td>\n",
              "      <td>2.68</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>stroke</th>\n",
              "      <td>2.68</td>\n",
              "      <td>2.68</td>\n",
              "      <td>3.47</td>\n",
              "      <td>3.4</td>\n",
              "      <td>3.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>compressionratio</th>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>10</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>horsepower</th>\n",
              "      <td>111</td>\n",
              "      <td>111</td>\n",
              "      <td>154</td>\n",
              "      <td>102</td>\n",
              "      <td>115</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>peakrpm</th>\n",
              "      <td>5000</td>\n",
              "      <td>5000</td>\n",
              "      <td>5000</td>\n",
              "      <td>5500</td>\n",
              "      <td>5500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>citympg</th>\n",
              "      <td>21</td>\n",
              "      <td>21</td>\n",
              "      <td>19</td>\n",
              "      <td>24</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>highwaympg</th>\n",
              "      <td>27</td>\n",
              "      <td>27</td>\n",
              "      <td>26</td>\n",
              "      <td>30</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>price</th>\n",
              "      <td>13495</td>\n",
              "      <td>16500</td>\n",
              "      <td>16500</td>\n",
              "      <td>13950</td>\n",
              "      <td>17450</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                   0  ...           4\n",
              "car_ID                             1  ...           5\n",
              "symboling                          3  ...           2\n",
              "CarName           alfa-romero giulia  ...  audi 100ls\n",
              "fueltype                         gas  ...         gas\n",
              "aspiration                       std  ...         std\n",
              "doornumber                       two  ...        four\n",
              "carbody                  convertible  ...       sedan\n",
              "drivewheel                       rwd  ...         4wd\n",
              "enginelocation                 front  ...       front\n",
              "wheelbase                       88.6  ...        99.4\n",
              "carlength                      168.8  ...       176.6\n",
              "carwidth                        64.1  ...        66.4\n",
              "carheight                       48.8  ...        54.3\n",
              "curbweight                      2548  ...        2824\n",
              "enginetype                      dohc  ...         ohc\n",
              "cylindernumber                  four  ...        five\n",
              "enginesize                       130  ...         136\n",
              "fuelsystem                      mpfi  ...        mpfi\n",
              "boreratio                       3.47  ...        3.19\n",
              "stroke                          2.68  ...         3.4\n",
              "compressionratio                   9  ...           8\n",
              "horsepower                       111  ...         115\n",
              "peakrpm                         5000  ...        5500\n",
              "citympg                           21  ...          18\n",
              "highwaympg                        27  ...          22\n",
              "price                          13495  ...       17450\n",
              "\n",
              "[26 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EpI03Nhf7tOF",
        "outputId": "4d2e2b65-d17e-49a8-ecce-7f5564e1f077"
      },
      "source": [
        "data_dict['Unnamed: 11'].T   # tells us which is categorical vs numerical"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0                                                   NaN\n",
              "1                                                   NaN\n",
              "2                                                   NaN\n",
              "3              Unique id of each observation (Interger)\n",
              "4     Its assigned insurance risk rating, A value of...\n",
              "5                     Name of car company (Categorical)\n",
              "6         Car fuel type i.e gas or diesel (Categorical)\n",
              "7                Aspiration used in a car (Categorical)\n",
              "8                Number of doors in a car (Categorical)\n",
              "9                             body of car (Categorical)\n",
              "10                    type of drive wheel (Categorical)\n",
              "11                 Location of car engine (Categorical)\n",
              "12                            Weelbase of car (Numeric)\n",
              "13                              Length of car (Numeric)\n",
              "14                               Width of car (Numeric)\n",
              "15                              height of car (Numeric)\n",
              "16    The weight of a car without occupants or bagga...\n",
              "17                        Type of engine. (Categorical)\n",
              "18             cylinder placed in the car (Categorical)\n",
              "19                                Size of car (Numeric)\n",
              "20                     Fuel system of car (Categorical)\n",
              "21                           Boreratio of car (Numeric)\n",
              "22         Stroke or volume inside the engine (Numeric)\n",
              "23                   compression ratio of car (Numeric)\n",
              "24                                 Horsepower (Numeric)\n",
              "25                               car peak rpm (Numeric)\n",
              "26                            Mileage in city (Numeric)\n",
              "27                         Mileage on highway (Numeric)\n",
              "28                               Price of car (Numeric)\n",
              "29                                                  NaN\n",
              "30                                                  NaN\n",
              "Name: Unnamed: 11, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fiZkNjdNSRD_"
      },
      "source": [
        "### **Making a separate categoricals dataframe**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "tpZ8hmQn7xd7",
        "outputId": "f8d48499-7160-4102-cdfa-efbf51f341fa"
      },
      "source": [
        "# Concatenating all categorical features\n",
        "\n",
        "categoricals = pd.concat((dataframe.iloc[:,2:9], dataframe.iloc[:,14:16], dataframe.iloc[:,17]),axis = 1)\n",
        "categoricals"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CarName</th>\n",
              "      <th>fueltype</th>\n",
              "      <th>aspiration</th>\n",
              "      <th>doornumber</th>\n",
              "      <th>carbody</th>\n",
              "      <th>drivewheel</th>\n",
              "      <th>enginelocation</th>\n",
              "      <th>enginetype</th>\n",
              "      <th>cylindernumber</th>\n",
              "      <th>fuelsystem</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>alfa-romero giulia</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>dohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>alfa-romero stelvio</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>dohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>alfa-romero Quadrifoglio</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>six</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>audi 100 ls</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>fwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>audi 100ls</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>4wd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>five</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>volvo 145e (sw)</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>volvo 144ea</td>\n",
              "      <td>gas</td>\n",
              "      <td>turbo</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>volvo 244dl</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>six</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>volvo 246</td>\n",
              "      <td>diesel</td>\n",
              "      <td>turbo</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>six</td>\n",
              "      <td>idi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>volvo 264gl</td>\n",
              "      <td>gas</td>\n",
              "      <td>turbo</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>205 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      CarName fueltype  ... cylindernumber fuelsystem\n",
              "0          alfa-romero giulia      gas  ...           four       mpfi\n",
              "1         alfa-romero stelvio      gas  ...           four       mpfi\n",
              "2    alfa-romero Quadrifoglio      gas  ...            six       mpfi\n",
              "3                 audi 100 ls      gas  ...           four       mpfi\n",
              "4                  audi 100ls      gas  ...           five       mpfi\n",
              "..                        ...      ...  ...            ...        ...\n",
              "200           volvo 145e (sw)      gas  ...           four       mpfi\n",
              "201               volvo 144ea      gas  ...           four       mpfi\n",
              "202               volvo 244dl      gas  ...            six       mpfi\n",
              "203                 volvo 246   diesel  ...            six        idi\n",
              "204               volvo 264gl      gas  ...           four       mpfi\n",
              "\n",
              "[205 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        },
        "id": "JGzPTVNt0Yu-",
        "outputId": "249f769b-6f5a-429b-a6f9-edbbb48ffcb9"
      },
      "source": [
        "categoricals.head()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CarName</th>\n",
              "      <th>fueltype</th>\n",
              "      <th>aspiration</th>\n",
              "      <th>doornumber</th>\n",
              "      <th>carbody</th>\n",
              "      <th>drivewheel</th>\n",
              "      <th>enginelocation</th>\n",
              "      <th>enginetype</th>\n",
              "      <th>cylindernumber</th>\n",
              "      <th>fuelsystem</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>alfa-romero giulia</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>dohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>alfa-romero stelvio</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>convertible</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>dohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>alfa-romero Quadrifoglio</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>two</td>\n",
              "      <td>hatchback</td>\n",
              "      <td>rwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohcv</td>\n",
              "      <td>six</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>audi 100 ls</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>fwd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>four</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>audi 100ls</td>\n",
              "      <td>gas</td>\n",
              "      <td>std</td>\n",
              "      <td>four</td>\n",
              "      <td>sedan</td>\n",
              "      <td>4wd</td>\n",
              "      <td>front</td>\n",
              "      <td>ohc</td>\n",
              "      <td>five</td>\n",
              "      <td>mpfi</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    CarName fueltype  ... cylindernumber fuelsystem\n",
              "0        alfa-romero giulia      gas  ...           four       mpfi\n",
              "1       alfa-romero stelvio      gas  ...           four       mpfi\n",
              "2  alfa-romero Quadrifoglio      gas  ...            six       mpfi\n",
              "3               audi 100 ls      gas  ...           four       mpfi\n",
              "4                audi 100ls      gas  ...           five       mpfi\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vi3h4rBG8rop",
        "outputId": "deb8662f-0b66-47d8-a266-6b8116ca2904"
      },
      "source": [
        "dataframe.shape"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(205, 26)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "RbJg9hw9zX7r",
        "outputId": "a3307159-4380-40f6-ca07-f6ade004c179"
      },
      "source": [
        "pd.get_dummies(categoricals)    # alternative of one hot"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CarName_Nissan versa</th>\n",
              "      <th>CarName_alfa-romero Quadrifoglio</th>\n",
              "      <th>CarName_alfa-romero giulia</th>\n",
              "      <th>CarName_alfa-romero stelvio</th>\n",
              "      <th>CarName_audi 100 ls</th>\n",
              "      <th>CarName_audi 100ls</th>\n",
              "      <th>CarName_audi 4000</th>\n",
              "      <th>CarName_audi 5000</th>\n",
              "      <th>CarName_audi 5000s (diesel)</th>\n",
              "      <th>CarName_audi fox</th>\n",
              "      <th>CarName_bmw 320i</th>\n",
              "      <th>CarName_bmw x1</th>\n",
              "      <th>CarName_bmw x3</th>\n",
              "      <th>CarName_bmw x4</th>\n",
              "      <th>CarName_bmw x5</th>\n",
              "      <th>CarName_bmw z4</th>\n",
              "      <th>CarName_buick century</th>\n",
              "      <th>CarName_buick century luxus (sw)</th>\n",
              "      <th>CarName_buick century special</th>\n",
              "      <th>CarName_buick electra 225 custom</th>\n",
              "      <th>CarName_buick opel isuzu deluxe</th>\n",
              "      <th>CarName_buick regal sport coupe (turbo)</th>\n",
              "      <th>CarName_buick skyhawk</th>\n",
              "      <th>CarName_buick skylark</th>\n",
              "      <th>CarName_chevrolet impala</th>\n",
              "      <th>CarName_chevrolet monte carlo</th>\n",
              "      <th>CarName_chevrolet vega 2300</th>\n",
              "      <th>CarName_dodge challenger se</th>\n",
              "      <th>CarName_dodge colt (sw)</th>\n",
              "      <th>CarName_dodge colt hardtop</th>\n",
              "      <th>CarName_dodge coronet custom</th>\n",
              "      <th>CarName_dodge coronet custom (sw)</th>\n",
              "      <th>CarName_dodge d200</th>\n",
              "      <th>CarName_dodge dart custom</th>\n",
              "      <th>CarName_dodge monaco (sw)</th>\n",
              "      <th>CarName_dodge rampage</th>\n",
              "      <th>CarName_honda accord</th>\n",
              "      <th>CarName_honda accord cvcc</th>\n",
              "      <th>CarName_honda accord lx</th>\n",
              "      <th>CarName_honda civic</th>\n",
              "      <th>...</th>\n",
              "      <th>CarName_vw dasher</th>\n",
              "      <th>CarName_vw rabbit</th>\n",
              "      <th>fueltype_diesel</th>\n",
              "      <th>fueltype_gas</th>\n",
              "      <th>aspiration_std</th>\n",
              "      <th>aspiration_turbo</th>\n",
              "      <th>doornumber_four</th>\n",
              "      <th>doornumber_two</th>\n",
              "      <th>carbody_convertible</th>\n",
              "      <th>carbody_hardtop</th>\n",
              "      <th>carbody_hatchback</th>\n",
              "      <th>carbody_sedan</th>\n",
              "      <th>carbody_wagon</th>\n",
              "      <th>drivewheel_4wd</th>\n",
              "      <th>drivewheel_fwd</th>\n",
              "      <th>drivewheel_rwd</th>\n",
              "      <th>enginelocation_front</th>\n",
              "      <th>enginelocation_rear</th>\n",
              "      <th>enginetype_dohc</th>\n",
              "      <th>enginetype_dohcv</th>\n",
              "      <th>enginetype_l</th>\n",
              "      <th>enginetype_ohc</th>\n",
              "      <th>enginetype_ohcf</th>\n",
              "      <th>enginetype_ohcv</th>\n",
              "      <th>enginetype_rotor</th>\n",
              "      <th>cylindernumber_eight</th>\n",
              "      <th>cylindernumber_five</th>\n",
              "      <th>cylindernumber_four</th>\n",
              "      <th>cylindernumber_six</th>\n",
              "      <th>cylindernumber_three</th>\n",
              "      <th>cylindernumber_twelve</th>\n",
              "      <th>cylindernumber_two</th>\n",
              "      <th>fuelsystem_1bbl</th>\n",
              "      <th>fuelsystem_2bbl</th>\n",
              "      <th>fuelsystem_4bbl</th>\n",
              "      <th>fuelsystem_idi</th>\n",
              "      <th>fuelsystem_mfi</th>\n",
              "      <th>fuelsystem_mpfi</th>\n",
              "      <th>fuelsystem_spdi</th>\n",
              "      <th>fuelsystem_spfi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>...</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>...</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>...</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>205 rows × 185 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     CarName_Nissan versa  ...  fuelsystem_spfi\n",
              "0                       0  ...                0\n",
              "1                       0  ...                0\n",
              "2                       0  ...                0\n",
              "3                       0  ...                0\n",
              "4                       0  ...                0\n",
              "..                    ...  ...              ...\n",
              "200                     0  ...                0\n",
              "201                     0  ...                0\n",
              "202                     0  ...                0\n",
              "203                     0  ...                0\n",
              "204                     0  ...                0\n",
              "\n",
              "[205 rows x 185 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U0SM1fS1107z"
      },
      "source": [
        "target_prices = dataframe['price']"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3icgZAqLUtdH"
      },
      "source": [
        "### **Removing Unnecessary Features**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S_JJcwH516_i"
      },
      "source": [
        "dataframe2 = dataframe.drop(['car_ID' , 'price'] , axis = 1)"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j8ZlCHOASlZm"
      },
      "source": [
        "## **Splitting Data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "deAtEZP_2eff"
      },
      "source": [
        "# Splitting data first  (dataframe 2 is all of our data)\n",
        "\n",
        "train_len = len(dataframe2)*7//10\n",
        "test_len = len(dataframe2) - train_len"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MJkx7tsg3HXD"
      },
      "source": [
        "train_data = dataframe2[0 : train_len].copy()\n",
        "test_data = dataframe2[train_len : train_len + test_len].copy()"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bEgb7UpJ3Hjt"
      },
      "source": [
        "train_prices = target_prices[0 : train_len].copy()\n",
        "test_prices = target_prices[train_len : train_len + test_len].copy()"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "85lkoiF63f88",
        "outputId": "40db0f5b-350b-4281-8e7b-fe98d639f94b"
      },
      "source": [
        "train_data.shape"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(143, 24)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UtHEx7ujSvrq"
      },
      "source": [
        "## **Normalizing Numerical Data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PFZ8YaFiU4oo"
      },
      "source": [
        "import numpy as np"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UEf3CytX3l0w"
      },
      "source": [
        "num_train_data = train_data.drop(categoricals.columns, axis = 1)\n",
        "num_test_data = test_data.drop(categoricals.columns, axis = 1)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jM29PqBy3l5V"
      },
      "source": [
        "mean = np.mean(num_train_data, axis = 0)\n",
        "std = np.std(num_train_data, axis = 0)\n",
        "\n",
        "num_train_data -= mean\n",
        "num_train_data /= std\n",
        "\n",
        "num_test_data -= mean\n",
        "num_test_data /= std"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DQ9jxzWy4RKN"
      },
      "source": [
        "train_data[num_train_data.columns] = num_train_data\n",
        "test_data[num_train_data.columns] = num_test_data"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DdYwaxhK7mZD"
      },
      "source": [
        "normalized_data = pd.concat((train_data, test_data))"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XpKwqjCjS8IJ"
      },
      "source": [
        "## **Encoding Categorical Data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "O7qXlzVT7mdz",
        "outputId": "8eec274d-49a5-4d52-eded-3338ae7ad4a1"
      },
      "source": [
        "pd.get_dummies(normalized_data, columns = categoricals.columns)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>symboling</th>\n",
              "      <th>wheelbase</th>\n",
              "      <th>carlength</th>\n",
              "      <th>carwidth</th>\n",
              "      <th>carheight</th>\n",
              "      <th>curbweight</th>\n",
              "      <th>enginesize</th>\n",
              "      <th>boreratio</th>\n",
              "      <th>stroke</th>\n",
              "      <th>compressionratio</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>peakrpm</th>\n",
              "      <th>citympg</th>\n",
              "      <th>highwaympg</th>\n",
              "      <th>CarName_Nissan versa</th>\n",
              "      <th>CarName_alfa-romero Quadrifoglio</th>\n",
              "      <th>CarName_alfa-romero giulia</th>\n",
              "      <th>CarName_alfa-romero stelvio</th>\n",
              "      <th>CarName_audi 100 ls</th>\n",
              "      <th>CarName_audi 100ls</th>\n",
              "      <th>CarName_audi 4000</th>\n",
              "      <th>CarName_audi 5000</th>\n",
              "      <th>CarName_audi 5000s (diesel)</th>\n",
              "      <th>CarName_audi fox</th>\n",
              "      <th>CarName_bmw 320i</th>\n",
              "      <th>CarName_bmw x1</th>\n",
              "      <th>CarName_bmw x3</th>\n",
              "      <th>CarName_bmw x4</th>\n",
              "      <th>CarName_bmw x5</th>\n",
              "      <th>CarName_bmw z4</th>\n",
              "      <th>CarName_buick century</th>\n",
              "      <th>CarName_buick century luxus (sw)</th>\n",
              "      <th>CarName_buick century special</th>\n",
              "      <th>CarName_buick electra 225 custom</th>\n",
              "      <th>CarName_buick opel isuzu deluxe</th>\n",
              "      <th>CarName_buick regal sport coupe (turbo)</th>\n",
              "      <th>CarName_buick skyhawk</th>\n",
              "      <th>CarName_buick skylark</th>\n",
              "      <th>CarName_chevrolet impala</th>\n",
              "      <th>CarName_chevrolet monte carlo</th>\n",
              "      <th>...</th>\n",
              "      <th>CarName_vw dasher</th>\n",
              "      <th>CarName_vw rabbit</th>\n",
              "      <th>fueltype_diesel</th>\n",
              "      <th>fueltype_gas</th>\n",
              "      <th>aspiration_std</th>\n",
              "      <th>aspiration_turbo</th>\n",
              "      <th>doornumber_four</th>\n",
              "      <th>doornumber_two</th>\n",
              "      <th>carbody_convertible</th>\n",
              "      <th>carbody_hardtop</th>\n",
              "      <th>carbody_hatchback</th>\n",
              "      <th>carbody_sedan</th>\n",
              "      <th>carbody_wagon</th>\n",
              "      <th>drivewheel_4wd</th>\n",
              "      <th>drivewheel_fwd</th>\n",
              "      <th>drivewheel_rwd</th>\n",
              "      <th>enginelocation_front</th>\n",
              "      <th>enginelocation_rear</th>\n",
              "      <th>enginetype_dohc</th>\n",
              "      <th>enginetype_dohcv</th>\n",
              "      <th>enginetype_l</th>\n",
              "      <th>enginetype_ohc</th>\n",
              "      <th>enginetype_ohcf</th>\n",
              "      <th>enginetype_ohcv</th>\n",
              "      <th>enginetype_rotor</th>\n",
              "      <th>cylindernumber_eight</th>\n",
              "      <th>cylindernumber_five</th>\n",
              "      <th>cylindernumber_four</th>\n",
              "      <th>cylindernumber_six</th>\n",
              "      <th>cylindernumber_three</th>\n",
              "      <th>cylindernumber_twelve</th>\n",
              "      <th>cylindernumber_two</th>\n",
              "      <th>fuelsystem_1bbl</th>\n",
              "      <th>fuelsystem_2bbl</th>\n",
              "      <th>fuelsystem_4bbl</th>\n",
              "      <th>fuelsystem_idi</th>\n",
              "      <th>fuelsystem_mfi</th>\n",
              "      <th>fuelsystem_mpfi</th>\n",
              "      <th>fuelsystem_spdi</th>\n",
              "      <th>fuelsystem_spfi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.024534</td>\n",
              "      <td>-0.604844</td>\n",
              "      <td>-0.175133</td>\n",
              "      <td>-0.203777</td>\n",
              "      <td>-0.388747</td>\n",
              "      <td>0.443696</td>\n",
              "      <td>0.466320</td>\n",
              "      <td>-2.312105</td>\n",
              "      <td>0.574871</td>\n",
              "      <td>-0.243696</td>\n",
              "      <td>1.102844</td>\n",
              "      <td>-0.379941</td>\n",
              "      <td>-0.824536</td>\n",
              "      <td>-0.611860</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.852552</td>\n",
              "      <td>0.198400</td>\n",
              "      <td>0.223563</td>\n",
              "      <td>0.092276</td>\n",
              "      <td>0.346786</td>\n",
              "      <td>-0.401172</td>\n",
              "      <td>-0.449782</td>\n",
              "      <td>-0.463384</td>\n",
              "      <td>0.361030</td>\n",
              "      <td>0.035271</td>\n",
              "      <td>-0.124078</td>\n",
              "      <td>0.677093</td>\n",
              "      <td>-0.109071</td>\n",
              "      <td>-0.055447</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.852552</td>\n",
              "      <td>0.137778</td>\n",
              "      <td>0.223563</td>\n",
              "      <td>0.176863</td>\n",
              "      <td>0.346786</td>\n",
              "      <td>0.445434</td>\n",
              "      <td>0.125444</td>\n",
              "      <td>-0.463384</td>\n",
              "      <td>0.361030</td>\n",
              "      <td>-0.522662</td>\n",
              "      <td>0.182652</td>\n",
              "      <td>0.677093</td>\n",
              "      <td>-0.967629</td>\n",
              "      <td>-1.168274</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>-1.778706</td>\n",
              "      <td>1.607864</td>\n",
              "      <td>1.124319</td>\n",
              "      <td>1.234196</td>\n",
              "      <td>0.811334</td>\n",
              "      <td>0.667951</td>\n",
              "      <td>0.231968</td>\n",
              "      <td>1.675332</td>\n",
              "      <td>-0.402688</td>\n",
              "      <td>-0.104213</td>\n",
              "      <td>0.159058</td>\n",
              "      <td>0.465686</td>\n",
              "      <td>-0.252164</td>\n",
              "      <td>-0.333653</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>-1.778706</td>\n",
              "      <td>1.607864</td>\n",
              "      <td>1.124319</td>\n",
              "      <td>1.191902</td>\n",
              "      <td>0.811334</td>\n",
              "      <td>0.836577</td>\n",
              "      <td>0.231968</td>\n",
              "      <td>1.675332</td>\n",
              "      <td>-0.402688</td>\n",
              "      <td>-0.327386</td>\n",
              "      <td>1.244411</td>\n",
              "      <td>0.254279</td>\n",
              "      <td>-0.824536</td>\n",
              "      <td>-0.750964</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>-1.778706</td>\n",
              "      <td>1.607864</td>\n",
              "      <td>1.124319</td>\n",
              "      <td>1.234196</td>\n",
              "      <td>0.811334</td>\n",
              "      <td>0.772255</td>\n",
              "      <td>0.913718</td>\n",
              "      <td>0.950343</td>\n",
              "      <td>-1.258051</td>\n",
              "      <td>-0.299489</td>\n",
              "      <td>0.630951</td>\n",
              "      <td>0.677093</td>\n",
              "      <td>-0.967629</td>\n",
              "      <td>-1.029170</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>...</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>-1.778706</td>\n",
              "      <td>1.607864</td>\n",
              "      <td>1.124319</td>\n",
              "      <td>1.234196</td>\n",
              "      <td>0.811334</td>\n",
              "      <td>1.128630</td>\n",
              "      <td>0.317187</td>\n",
              "      <td>-1.115874</td>\n",
              "      <td>0.361030</td>\n",
              "      <td>3.661836</td>\n",
              "      <td>-0.029700</td>\n",
              "      <td>-0.802754</td>\n",
              "      <td>0.177115</td>\n",
              "      <td>-0.472757</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>-1.778706</td>\n",
              "      <td>1.607864</td>\n",
              "      <td>1.124319</td>\n",
              "      <td>1.234196</td>\n",
              "      <td>0.811334</td>\n",
              "      <td>0.859176</td>\n",
              "      <td>0.231968</td>\n",
              "      <td>1.675332</td>\n",
              "      <td>-0.402688</td>\n",
              "      <td>-0.104213</td>\n",
              "      <td>0.159058</td>\n",
              "      <td>0.465686</td>\n",
              "      <td>-0.824536</td>\n",
              "      <td>-0.750964</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>205 rows × 199 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     symboling  wheelbase  ...  fuelsystem_spdi  fuelsystem_spfi\n",
              "0     1.729638  -1.499020  ...                0                0\n",
              "1     1.729638  -1.499020  ...                0                0\n",
              "2    -0.024534  -0.604844  ...                0                0\n",
              "3     0.852552   0.198400  ...                0                0\n",
              "4     0.852552   0.137778  ...                0                0\n",
              "..         ...        ...  ...              ...              ...\n",
              "200  -1.778706   1.607864  ...                0                0\n",
              "201  -1.778706   1.607864  ...                0                0\n",
              "202  -1.778706   1.607864  ...                0                0\n",
              "203  -1.778706   1.607864  ...                0                0\n",
              "204  -1.778706   1.607864  ...                0                0\n",
              "\n",
              "[205 rows x 199 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XersUfzo7miz"
      },
      "source": [
        "data_fin = pd.get_dummies(normalized_data, columns = categoricals.columns)"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sJwbb2-aTNTI"
      },
      "source": [
        "## **Splitting completely prepocessed data now**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dR30RCU38Nd1"
      },
      "source": [
        "train_data_fin = data_fin[0 : train_len].copy()\n",
        "test_data_fin = data_fin[train_len : train_len + test_len].copy()"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pqQCacFa8Nhw",
        "outputId": "da3343c3-76d5-40cc-85bb-9c9226606b07"
      },
      "source": [
        "train_data_fin.shape , test_data_fin.shape"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((143, 199), (62, 199))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q1uq4-Ru6E76"
      },
      "source": [
        "train_data = np.array(train_data_fin).astype('float32')\n",
        "train_prices = np.array(train_prices).astype('float32')\n",
        "\n",
        "test_data = np.array(test_data_fin).astype('float32')\n",
        "test_prices = np.array(test_prices).astype('float32')"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dw9KXBRZ6FJA",
        "outputId": "38a5d877-2b7e-46d3-bf81-ca18702aca6e"
      },
      "source": [
        "train_data.shape , test_data.shape , train_prices.shape, test_prices.shape"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((143, 199), (62, 199), (143,), (62,))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L4Wc49QeThBM"
      },
      "source": [
        "## **Building and Compiling a Model**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gkKJ0gXbDvh_"
      },
      "source": [
        "# Now making a model:\n",
        "\n",
        "from keras import models, layers, regularizers\n",
        "\n",
        "def build_model():\n",
        "  model = models.Sequential()\n",
        "  \n",
        "  model.add(layers.Dense(256, activation = 'relu', kernel_regularizer = regularizers.l2(0.001), input_shape = (199,)))\n",
        "  model.add(layers.Dropout(0.3))\n",
        "  model.add(layers.Dense(256, activation = 'relu', kernel_regularizer = regularizers.l2(0.001)))\n",
        "  model.add(layers.Dropout(0.3))\n",
        "  model.add(layers.Dense(16, activation = 'relu', kernel_regularizer = regularizers.l2(0.001)))\n",
        "  model.add(layers.Dropout(0.3))\n",
        "  \n",
        "  model.add(layers.Dense(1))\n",
        "\n",
        "\n",
        "  model.compile(optimizer = 'rmsprop', loss = 'mse', metrics = ['mae'])\n",
        "  return model"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a73U5rCcTqvN"
      },
      "source": [
        "## **Validating Our Approach AND Training the Model**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NZRy2lGOD0UP",
        "outputId": "c38e49c8-fbc6-4451-94bb-d777119a850b"
      },
      "source": [
        "k = 5\n",
        "number_of_validation_samples = len(train_data)//k\n",
        "\n",
        "number_of_epochs = 100\n",
        "all_scores = []\n",
        "\n",
        "for i in range(k):\n",
        "  print('processing fold #', i)\n",
        "  val_data_k = train_data[i*number_of_validation_samples : (i+1) * number_of_validation_samples]        # Prepares the validation data from partition #k\n",
        "  val_prices_k = train_prices[i*number_of_validation_samples : (i+1) * number_of_validation_samples]\n",
        "\n",
        "  partial_train_data_k = np.concatenate( ( train_data[ : i*number_of_validation_samples],              # Prepares the training data from all other partitions\n",
        "                                         train_data[(i+1)*number_of_validation_samples : ] ) , axis = 0 )\n",
        "  \n",
        "  partial_train_prices_k = np.concatenate( ( train_prices[ : i*number_of_validation_samples], \n",
        "                                         train_prices[(i+1)*number_of_validation_samples : ] ) , axis = 0 )\n",
        "  \n",
        "  modelC = build_model()  # builds keras model (already compiled) --> remember the function we made\n",
        "\n",
        "  historyC = modelC.fit(partial_train_data_k,\n",
        "             partial_train_prices_k,\n",
        "             epochs = number_of_epochs,\n",
        "             batch_size = 8, \n",
        "             verbose = 1,  # -->    verbose: 0, 1, or 2  --> 0 = silent, 1 = progress bar, 2 = one line per epoch. \n",
        "             validation_data = (val_data_k, val_prices_k) )\n",
        "  \n",
        "\n",
        "  \n",
        "  #val_loss , val_accuracy = modelI.evaluate(val_data, val_labels, verbose = 1)  # basically ( val_loss , val_accuracy ) if you compare it\n",
        "\n",
        "  #all_scores.append(val_accuracy)  # --> gives us list of scores that all the 'k' validation sets got, w8 where's our test data\n",
        "\n",
        "#all_scores"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "processing fold # 0\n",
            "Epoch 1/100\n",
            "15/15 [==============================] - 1s 33ms/step - loss: 280613201.0000 - mae: 14123.7372 - val_loss: 339812064.0000 - val_mae: 15957.2061\n",
            "Epoch 2/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 282634779.0000 - mae: 13839.8502 - val_loss: 336677376.0000 - val_mae: 15864.3252\n",
            "Epoch 3/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 267563103.0000 - mae: 13912.1185 - val_loss: 329477440.0000 - val_mae: 15652.8604\n",
            "Epoch 4/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 251969095.0000 - mae: 13358.5214 - val_loss: 316227488.0000 - val_mae: 15269.4629\n",
            "Epoch 5/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 252087643.0000 - mae: 13153.5338 - val_loss: 297423968.0000 - val_mae: 14711.3770\n",
            "Epoch 6/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 227545077.0000 - mae: 12339.4390 - val_loss: 271154080.0000 - val_mae: 13914.7568\n",
            "Epoch 7/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 236565763.0000 - mae: 12002.1552 - val_loss: 236332544.0000 - val_mae: 12812.6064\n",
            "Epoch 8/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 161502723.5000 - mae: 9425.7297 - val_loss: 192845696.0000 - val_mae: 11336.6074\n",
            "Epoch 9/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 163441497.0000 - mae: 9031.6412 - val_loss: 156239888.0000 - val_mae: 9917.1748\n",
            "Epoch 10/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 106591214.7500 - mae: 6871.0511 - val_loss: 115015384.0000 - val_mae: 8140.1831\n",
            "Epoch 11/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 73595247.1250 - mae: 5213.5877 - val_loss: 80925488.0000 - val_mae: 6469.2627\n",
            "Epoch 12/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 55193913.5000 - mae: 4759.9380 - val_loss: 51422808.0000 - val_mae: 4883.5298\n",
            "Epoch 13/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 35967465.3750 - mae: 3936.7538 - val_loss: 39805308.0000 - val_mae: 4228.8257\n",
            "Epoch 14/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 52395592.8750 - mae: 4749.9892 - val_loss: 35576960.0000 - val_mae: 4089.3567\n",
            "Epoch 15/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 37642210.7031 - mae: 4069.2978 - val_loss: 30249158.0000 - val_mae: 3765.8689\n",
            "Epoch 16/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 38335758.7500 - mae: 4335.1667 - val_loss: 24771052.0000 - val_mae: 3390.7625\n",
            "Epoch 17/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16989402.6250 - mae: 2920.9730 - val_loss: 24493956.0000 - val_mae: 3392.1758\n",
            "Epoch 18/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 41824527.2500 - mae: 4833.2353 - val_loss: 26476518.0000 - val_mae: 3640.0623\n",
            "Epoch 19/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26384309.1250 - mae: 3208.3106 - val_loss: 23604998.0000 - val_mae: 3414.6121\n",
            "Epoch 20/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 37881419.8750 - mae: 4128.0706 - val_loss: 25211430.0000 - val_mae: 3610.7512\n",
            "Epoch 21/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18596836.8750 - mae: 3169.4039 - val_loss: 22262060.0000 - val_mae: 3325.1702\n",
            "Epoch 22/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23788473.6875 - mae: 3358.9748 - val_loss: 24381184.0000 - val_mae: 3573.3972\n",
            "Epoch 23/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19473070.5000 - mae: 3139.9437 - val_loss: 23569090.0000 - val_mae: 3475.5093\n",
            "Epoch 24/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 25923355.2500 - mae: 3523.8597 - val_loss: 20386402.0000 - val_mae: 3156.8301\n",
            "Epoch 25/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18320326.5625 - mae: 3142.4861 - val_loss: 23735274.0000 - val_mae: 3488.4045\n",
            "Epoch 26/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25073700.1250 - mae: 3523.2397 - val_loss: 18067724.0000 - val_mae: 2961.7632\n",
            "Epoch 27/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25545016.2500 - mae: 3493.6972 - val_loss: 17981846.0000 - val_mae: 2941.0710\n",
            "Epoch 28/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 18946730.4375 - mae: 3074.9993 - val_loss: 13201896.0000 - val_mae: 2506.3320\n",
            "Epoch 29/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 17951529.0000 - mae: 3142.7634 - val_loss: 14824185.0000 - val_mae: 2683.3567\n",
            "Epoch 30/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 17331976.5625 - mae: 3108.3051 - val_loss: 19603998.0000 - val_mae: 3060.2932\n",
            "Epoch 31/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 20586193.5625 - mae: 3011.4944 - val_loss: 16604555.0000 - val_mae: 2785.9067\n",
            "Epoch 32/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14340946.6250 - mae: 2516.9765 - val_loss: 18876342.0000 - val_mae: 2957.4500\n",
            "Epoch 33/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 12235555.8125 - mae: 2533.8487 - val_loss: 18623948.0000 - val_mae: 2871.9290\n",
            "Epoch 34/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 12330518.6562 - mae: 2656.3273 - val_loss: 19267526.0000 - val_mae: 2951.1130\n",
            "Epoch 35/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15268187.3750 - mae: 2736.5963 - val_loss: 17542504.0000 - val_mae: 2790.4050\n",
            "Epoch 36/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12683564.1250 - mae: 2510.8867 - val_loss: 16719871.0000 - val_mae: 2670.0374\n",
            "Epoch 37/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14221493.5938 - mae: 2503.7744 - val_loss: 15664291.0000 - val_mae: 2569.6453\n",
            "Epoch 38/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17649017.9375 - mae: 3056.3765 - val_loss: 17394274.0000 - val_mae: 2777.7654\n",
            "Epoch 39/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17780606.6875 - mae: 2979.4982 - val_loss: 17800990.0000 - val_mae: 2817.4041\n",
            "Epoch 40/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17555559.6250 - mae: 2806.5224 - val_loss: 20796806.0000 - val_mae: 3111.2869\n",
            "Epoch 41/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 23201183.0938 - mae: 3135.1944 - val_loss: 22200678.0000 - val_mae: 3251.3677\n",
            "Epoch 42/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14073178.0625 - mae: 2802.6989 - val_loss: 19506766.0000 - val_mae: 2988.6262\n",
            "Epoch 43/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17347447.5625 - mae: 2844.9183 - val_loss: 17640284.0000 - val_mae: 2871.2429\n",
            "Epoch 44/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17422289.8750 - mae: 2791.9047 - val_loss: 17025486.0000 - val_mae: 2743.6472\n",
            "Epoch 45/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12024189.1250 - mae: 2329.3998 - val_loss: 13275898.0000 - val_mae: 2341.2620\n",
            "Epoch 46/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17391037.3125 - mae: 2837.2560 - val_loss: 14828649.0000 - val_mae: 2547.6072\n",
            "Epoch 47/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15841615.6250 - mae: 2850.4873 - val_loss: 15402497.0000 - val_mae: 2641.3904\n",
            "Epoch 48/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18266008.3125 - mae: 2892.7036 - val_loss: 12052795.0000 - val_mae: 2327.2517\n",
            "Epoch 49/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14525168.0000 - mae: 2655.5614 - val_loss: 16308610.0000 - val_mae: 2781.1238\n",
            "Epoch 50/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13484698.5000 - mae: 2691.3405 - val_loss: 16489411.0000 - val_mae: 2720.6831\n",
            "Epoch 51/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 23944287.3750 - mae: 3529.8741 - val_loss: 18829612.0000 - val_mae: 2916.1655\n",
            "Epoch 52/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 20947048.4375 - mae: 3157.2781 - val_loss: 16947914.0000 - val_mae: 2721.7637\n",
            "Epoch 53/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14354153.8125 - mae: 2531.9996 - val_loss: 12854999.0000 - val_mae: 2366.2676\n",
            "Epoch 54/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 12918113.5625 - mae: 2458.0530 - val_loss: 13483851.0000 - val_mae: 2415.3430\n",
            "Epoch 55/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14550752.4688 - mae: 2569.8599 - val_loss: 14954919.0000 - val_mae: 2580.0222\n",
            "Epoch 56/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 15709886.0938 - mae: 2657.3175 - val_loss: 10869986.0000 - val_mae: 2228.4841\n",
            "Epoch 57/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 13918200.3438 - mae: 2670.6507 - val_loss: 13334666.0000 - val_mae: 2505.8359\n",
            "Epoch 58/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 9244407.8125 - mae: 2350.4056 - val_loss: 11906113.0000 - val_mae: 2314.9556\n",
            "Epoch 59/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12163383.0625 - mae: 2717.4883 - val_loss: 11619968.0000 - val_mae: 2246.6528\n",
            "Epoch 60/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17338960.7500 - mae: 2686.6919 - val_loss: 12645499.0000 - val_mae: 2375.6140\n",
            "Epoch 61/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 10981184.3125 - mae: 2477.3793 - val_loss: 12559266.0000 - val_mae: 2348.4592\n",
            "Epoch 62/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14542931.3125 - mae: 2485.1374 - val_loss: 12179933.0000 - val_mae: 2311.4353\n",
            "Epoch 63/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14153049.4062 - mae: 2712.6649 - val_loss: 19816830.0000 - val_mae: 3040.8374\n",
            "Epoch 64/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19750716.5000 - mae: 3049.7714 - val_loss: 20268958.0000 - val_mae: 3096.9871\n",
            "Epoch 65/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 22252460.0625 - mae: 2943.2385 - val_loss: 15616186.0000 - val_mae: 2753.1521\n",
            "Epoch 66/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12636640.8438 - mae: 2522.0194 - val_loss: 15957455.0000 - val_mae: 2764.1016\n",
            "Epoch 67/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19409157.3125 - mae: 2885.3010 - val_loss: 21128118.0000 - val_mae: 3241.9121\n",
            "Epoch 68/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24408717.7500 - mae: 3044.9016 - val_loss: 13325959.0000 - val_mae: 2484.6335\n",
            "Epoch 69/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 23672537.1250 - mae: 3265.9216 - val_loss: 16755254.0000 - val_mae: 2757.1956\n",
            "Epoch 70/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10114686.2031 - mae: 2387.2401 - val_loss: 15561345.0000 - val_mae: 2698.2629\n",
            "Epoch 71/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 12348866.0938 - mae: 2405.1597 - val_loss: 15732037.0000 - val_mae: 2628.3972\n",
            "Epoch 72/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 11676321.6875 - mae: 2562.7191 - val_loss: 19518814.0000 - val_mae: 2997.4219\n",
            "Epoch 73/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11413244.0625 - mae: 2501.5861 - val_loss: 23104668.0000 - val_mae: 3305.2622\n",
            "Epoch 74/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10958994.5625 - mae: 2323.1994 - val_loss: 19177820.0000 - val_mae: 2901.7109\n",
            "Epoch 75/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 16480857.9688 - mae: 2638.4217 - val_loss: 16749731.0000 - val_mae: 2725.0271\n",
            "Epoch 76/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 17182746.0000 - mae: 2834.9378 - val_loss: 15217603.0000 - val_mae: 2644.2778\n",
            "Epoch 77/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 15049537.6875 - mae: 2803.5146 - val_loss: 17102812.0000 - val_mae: 2773.7695\n",
            "Epoch 78/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 9377990.9062 - mae: 2164.1288 - val_loss: 19030960.0000 - val_mae: 3024.2344\n",
            "Epoch 79/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20531999.0000 - mae: 2863.5275 - val_loss: 15120222.0000 - val_mae: 2648.7161\n",
            "Epoch 80/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18333415.0000 - mae: 2699.3245 - val_loss: 14275182.0000 - val_mae: 2513.3066\n",
            "Epoch 81/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14853525.8750 - mae: 2739.9131 - val_loss: 17482900.0000 - val_mae: 2886.7163\n",
            "Epoch 82/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15434198.5312 - mae: 2508.0765 - val_loss: 18294526.0000 - val_mae: 2936.4675\n",
            "Epoch 83/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19930143.1250 - mae: 2675.4661 - val_loss: 14872915.0000 - val_mae: 2615.1443\n",
            "Epoch 84/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11046177.1250 - mae: 2315.8212 - val_loss: 18270306.0000 - val_mae: 2948.6008\n",
            "Epoch 85/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13334194.0938 - mae: 2130.5207 - val_loss: 16891954.0000 - val_mae: 2780.2356\n",
            "Epoch 86/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14802503.3750 - mae: 2817.2213 - val_loss: 23078278.0000 - val_mae: 3274.9480\n",
            "Epoch 87/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13239386.4375 - mae: 2659.9648 - val_loss: 18942234.0000 - val_mae: 2895.2358\n",
            "Epoch 88/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10601494.9297 - mae: 2180.9545 - val_loss: 17439274.0000 - val_mae: 2784.2131\n",
            "Epoch 89/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 9301034.5312 - mae: 2173.1757 - val_loss: 13383593.0000 - val_mae: 2471.9172\n",
            "Epoch 90/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11978582.8750 - mae: 2584.7998 - val_loss: 19288142.0000 - val_mae: 2983.8750\n",
            "Epoch 91/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 17017153.6875 - mae: 2913.8882 - val_loss: 17056082.0000 - val_mae: 2774.7673\n",
            "Epoch 92/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 16433026.8750 - mae: 2836.1127 - val_loss: 17070766.0000 - val_mae: 2746.6555\n",
            "Epoch 93/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 7174043.1250 - mae: 1970.8322 - val_loss: 18306580.0000 - val_mae: 2906.0188\n",
            "Epoch 94/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18587206.1875 - mae: 3002.0942 - val_loss: 16827926.0000 - val_mae: 2762.4353\n",
            "Epoch 95/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13042675.2812 - mae: 2311.1706 - val_loss: 13575174.0000 - val_mae: 2548.0203\n",
            "Epoch 96/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14990926.0625 - mae: 2893.7824 - val_loss: 17338062.0000 - val_mae: 2823.0730\n",
            "Epoch 97/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12490125.1562 - mae: 2626.1961 - val_loss: 14436262.0000 - val_mae: 2635.9683\n",
            "Epoch 98/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13062346.5000 - mae: 2468.7050 - val_loss: 18518474.0000 - val_mae: 2952.5842\n",
            "Epoch 99/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 10209841.9375 - mae: 2098.6287 - val_loss: 18342842.0000 - val_mae: 2852.6726\n",
            "Epoch 100/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 19193933.5625 - mae: 3069.8085 - val_loss: 22695508.0000 - val_mae: 3223.5269\n",
            "processing fold # 1\n",
            "Epoch 1/100\n",
            "15/15 [==============================] - 1s 17ms/step - loss: 277091140.0000 - mae: 14322.0223 - val_loss: 193110112.0000 - val_mae: 11076.7451\n",
            "Epoch 2/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 274175366.0000 - mae: 14388.0719 - val_loss: 190564096.0000 - val_mae: 10987.2031\n",
            "Epoch 3/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 258581110.0000 - mae: 13790.0052 - val_loss: 185100432.0000 - val_mae: 10797.6670\n",
            "Epoch 4/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 281182642.0000 - mae: 14096.1337 - val_loss: 176356704.0000 - val_mae: 10501.0605\n",
            "Epoch 5/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 281915645.0000 - mae: 14184.6695 - val_loss: 164455584.0000 - val_mae: 10069.9707\n",
            "Epoch 6/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 253571129.0000 - mae: 13534.8234 - val_loss: 147075312.0000 - val_mae: 9438.3516\n",
            "Epoch 7/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 199024198.0000 - mae: 11740.2638 - val_loss: 123924088.0000 - val_mae: 8561.0381\n",
            "Epoch 8/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 183476254.0000 - mae: 11083.3617 - val_loss: 99425256.0000 - val_mae: 7538.9854\n",
            "Epoch 9/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 150003788.0000 - mae: 9489.5537 - val_loss: 73725328.0000 - val_mae: 6309.1992\n",
            "Epoch 10/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 111121118.0000 - mae: 7615.7871 - val_loss: 48814816.0000 - val_mae: 4904.4175\n",
            "Epoch 11/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 59968451.2500 - mae: 5567.3197 - val_loss: 31501472.0000 - val_mae: 3926.1367\n",
            "Epoch 12/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 60775656.2500 - mae: 5149.6336 - val_loss: 19815056.0000 - val_mae: 3101.3523\n",
            "Epoch 13/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 62617848.0000 - mae: 4530.1814 - val_loss: 13669858.0000 - val_mae: 2717.7307\n",
            "Epoch 14/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 30616863.6250 - mae: 3870.4752 - val_loss: 12483887.0000 - val_mae: 2703.7634\n",
            "Epoch 15/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 39863895.6250 - mae: 4321.2969 - val_loss: 11110607.0000 - val_mae: 2652.0374\n",
            "Epoch 16/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 47067754.2500 - mae: 4737.8266 - val_loss: 9566414.0000 - val_mae: 2558.9419\n",
            "Epoch 17/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 40630665.2500 - mae: 4649.8948 - val_loss: 10806687.0000 - val_mae: 2703.7395\n",
            "Epoch 18/100\n",
            "15/15 [==============================] - 0s 8ms/step - loss: 29306752.8750 - mae: 3835.5170 - val_loss: 10263661.0000 - val_mae: 2669.2046\n",
            "Epoch 19/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 33665565.2500 - mae: 3838.0380 - val_loss: 9341594.0000 - val_mae: 2584.9004\n",
            "Epoch 20/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 58724731.0000 - mae: 5193.7501 - val_loss: 10288139.0000 - val_mae: 2730.9456\n",
            "Epoch 21/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 18453537.5938 - mae: 3003.0573 - val_loss: 9126183.0000 - val_mae: 2599.1829\n",
            "Epoch 22/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 31111827.5000 - mae: 4233.4702 - val_loss: 8773638.0000 - val_mae: 2550.8533\n",
            "Epoch 23/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 38140330.8750 - mae: 4043.8235 - val_loss: 9425935.0000 - val_mae: 2646.7974\n",
            "Epoch 24/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 29078699.8750 - mae: 3666.1622 - val_loss: 9280274.0000 - val_mae: 2623.3464\n",
            "Epoch 25/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 40572020.6250 - mae: 4812.9597 - val_loss: 9130329.0000 - val_mae: 2598.1653\n",
            "Epoch 26/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 33374760.0000 - mae: 4279.9279 - val_loss: 7926628.0000 - val_mae: 2415.3574\n",
            "Epoch 27/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27879484.8750 - mae: 3800.2767 - val_loss: 7422135.0000 - val_mae: 2376.2815\n",
            "Epoch 28/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 30418172.8750 - mae: 3877.7177 - val_loss: 8082303.0000 - val_mae: 2439.7827\n",
            "Epoch 29/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26925811.8125 - mae: 3565.5191 - val_loss: 7894487.0000 - val_mae: 2438.1897\n",
            "Epoch 30/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 27591320.6875 - mae: 3519.1734 - val_loss: 8197399.5000 - val_mae: 2434.4634\n",
            "Epoch 31/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22254436.8125 - mae: 3219.0645 - val_loss: 8223863.5000 - val_mae: 2431.7468\n",
            "Epoch 32/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18242825.1875 - mae: 3183.3217 - val_loss: 7199567.0000 - val_mae: 2336.7109\n",
            "Epoch 33/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26607124.4688 - mae: 3742.3934 - val_loss: 6728383.5000 - val_mae: 2276.5071\n",
            "Epoch 34/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 22626821.8750 - mae: 3532.8858 - val_loss: 7056872.0000 - val_mae: 2343.0278\n",
            "Epoch 35/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 25863185.0000 - mae: 3792.6590 - val_loss: 7352815.5000 - val_mae: 2400.1438\n",
            "Epoch 36/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 31812781.7500 - mae: 4147.7163 - val_loss: 7880823.5000 - val_mae: 2480.9011\n",
            "Epoch 37/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27069710.5000 - mae: 3708.6179 - val_loss: 7278767.0000 - val_mae: 2403.7642\n",
            "Epoch 38/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 24729754.7500 - mae: 3701.2612 - val_loss: 7597793.0000 - val_mae: 2453.4529\n",
            "Epoch 39/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 16842305.7500 - mae: 2808.2626 - val_loss: 6747278.5000 - val_mae: 2302.2253\n",
            "Epoch 40/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17109987.2500 - mae: 3200.1175 - val_loss: 6163188.0000 - val_mae: 2189.6516\n",
            "Epoch 41/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 21042800.5625 - mae: 3111.3367 - val_loss: 7433299.5000 - val_mae: 2307.1221\n",
            "Epoch 42/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25038960.3750 - mae: 3559.2653 - val_loss: 6538536.0000 - val_mae: 2218.5652\n",
            "Epoch 43/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 37515084.1250 - mae: 4066.8771 - val_loss: 6119953.0000 - val_mae: 2184.8000\n",
            "Epoch 44/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23861961.0000 - mae: 3432.8091 - val_loss: 6522491.5000 - val_mae: 2234.6270\n",
            "Epoch 45/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 14302121.5625 - mae: 2808.6067 - val_loss: 5722966.5000 - val_mae: 2082.2998\n",
            "Epoch 46/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 21977899.1875 - mae: 3408.5332 - val_loss: 6230940.5000 - val_mae: 2204.6724\n",
            "Epoch 47/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25812784.8125 - mae: 3131.3024 - val_loss: 6424103.5000 - val_mae: 2210.4041\n",
            "Epoch 48/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 16022397.1250 - mae: 2933.5560 - val_loss: 6182956.5000 - val_mae: 2187.2932\n",
            "Epoch 49/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15272540.2188 - mae: 2862.5356 - val_loss: 5591018.5000 - val_mae: 2064.7715\n",
            "Epoch 50/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 21861407.3281 - mae: 3053.5749 - val_loss: 5686968.0000 - val_mae: 2081.9629\n",
            "Epoch 51/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 19585260.2500 - mae: 3342.5093 - val_loss: 6120174.5000 - val_mae: 2135.5581\n",
            "Epoch 52/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 18086968.3750 - mae: 2964.2928 - val_loss: 6488475.5000 - val_mae: 2181.7437\n",
            "Epoch 53/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16395071.9688 - mae: 2887.5441 - val_loss: 5187525.5000 - val_mae: 1945.0137\n",
            "Epoch 54/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17870916.3125 - mae: 3113.1066 - val_loss: 6114672.5000 - val_mae: 2100.9954\n",
            "Epoch 55/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17045077.5000 - mae: 2952.5862 - val_loss: 5116637.5000 - val_mae: 1943.8430\n",
            "Epoch 56/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11020328.0312 - mae: 2602.2871 - val_loss: 5611323.5000 - val_mae: 2048.5085\n",
            "Epoch 57/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 36761877.8750 - mae: 3545.7215 - val_loss: 5998688.5000 - val_mae: 2142.9917\n",
            "Epoch 58/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 23537530.0625 - mae: 3179.3338 - val_loss: 5786810.5000 - val_mae: 2043.6621\n",
            "Epoch 59/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24745364.8750 - mae: 3143.3781 - val_loss: 6267699.0000 - val_mae: 2204.0837\n",
            "Epoch 60/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12897374.3750 - mae: 2680.3437 - val_loss: 5841712.5000 - val_mae: 2098.1875\n",
            "Epoch 61/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 20693479.4375 - mae: 2974.6056 - val_loss: 5779551.5000 - val_mae: 2099.4907\n",
            "Epoch 62/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 18016932.7500 - mae: 2987.7428 - val_loss: 5663833.5000 - val_mae: 2073.6169\n",
            "Epoch 63/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 28928645.0000 - mae: 3705.4375 - val_loss: 5317569.0000 - val_mae: 1995.3352\n",
            "Epoch 64/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13605265.7500 - mae: 2740.1815 - val_loss: 5498272.5000 - val_mae: 2017.7002\n",
            "Epoch 65/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24512263.4375 - mae: 3295.9554 - val_loss: 4946311.0000 - val_mae: 1883.3245\n",
            "Epoch 66/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16000189.8438 - mae: 2719.5472 - val_loss: 5372082.5000 - val_mae: 1966.6437\n",
            "Epoch 67/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14598328.2188 - mae: 2711.6642 - val_loss: 5321169.0000 - val_mae: 1997.4139\n",
            "Epoch 68/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18132258.6562 - mae: 3054.3955 - val_loss: 5251352.0000 - val_mae: 1924.9852\n",
            "Epoch 69/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24350048.2500 - mae: 3503.4731 - val_loss: 6318587.5000 - val_mae: 2208.6206\n",
            "Epoch 70/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21965216.6875 - mae: 3182.2424 - val_loss: 6069715.0000 - val_mae: 2170.0115\n",
            "Epoch 71/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13525752.1406 - mae: 2693.9250 - val_loss: 6408852.0000 - val_mae: 2232.7878\n",
            "Epoch 72/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27299205.8750 - mae: 3399.0697 - val_loss: 5914867.0000 - val_mae: 2131.6963\n",
            "Epoch 73/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22483211.3750 - mae: 3170.4923 - val_loss: 5578912.5000 - val_mae: 2004.5297\n",
            "Epoch 74/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 21420460.2188 - mae: 3381.6162 - val_loss: 5947052.0000 - val_mae: 2106.1101\n",
            "Epoch 75/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12374901.2500 - mae: 2743.2832 - val_loss: 5590827.5000 - val_mae: 2032.9355\n",
            "Epoch 76/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17637603.8750 - mae: 2912.0959 - val_loss: 5704256.0000 - val_mae: 2092.2209\n",
            "Epoch 77/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 29089412.7500 - mae: 3802.0578 - val_loss: 5683877.0000 - val_mae: 2107.0317\n",
            "Epoch 78/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16705011.1250 - mae: 3120.5249 - val_loss: 5118232.0000 - val_mae: 1966.9023\n",
            "Epoch 79/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21010085.6250 - mae: 3177.5243 - val_loss: 4327902.0000 - val_mae: 1724.0812\n",
            "Epoch 80/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21426678.5625 - mae: 3067.7404 - val_loss: 4666975.5000 - val_mae: 1862.3701\n",
            "Epoch 81/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 22403502.1250 - mae: 3355.5618 - val_loss: 4568723.5000 - val_mae: 1775.1185\n",
            "Epoch 82/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10684030.6250 - mae: 2409.4853 - val_loss: 5316619.0000 - val_mae: 2008.8785\n",
            "Epoch 83/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19253644.4375 - mae: 3394.5445 - val_loss: 5583283.5000 - val_mae: 2045.8181\n",
            "Epoch 84/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 13742103.3594 - mae: 2697.3821 - val_loss: 5506563.0000 - val_mae: 2042.5120\n",
            "Epoch 85/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17548414.8750 - mae: 3079.8864 - val_loss: 5217373.0000 - val_mae: 2005.6432\n",
            "Epoch 86/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18601437.8750 - mae: 3389.4312 - val_loss: 4791290.5000 - val_mae: 1898.6183\n",
            "Epoch 87/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 13596229.2812 - mae: 2718.1694 - val_loss: 4513119.5000 - val_mae: 1786.4899\n",
            "Epoch 88/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 8582057.2969 - mae: 2117.8269 - val_loss: 4818521.0000 - val_mae: 1912.5593\n",
            "Epoch 89/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14147652.6875 - mae: 2932.3821 - val_loss: 4770541.0000 - val_mae: 1846.4023\n",
            "Epoch 90/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 15494365.3750 - mae: 2814.7385 - val_loss: 5505131.5000 - val_mae: 2064.4500\n",
            "Epoch 91/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 13613480.6875 - mae: 2775.7603 - val_loss: 5364357.5000 - val_mae: 2011.4697\n",
            "Epoch 92/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15104196.0312 - mae: 2717.1148 - val_loss: 5335488.0000 - val_mae: 1916.7812\n",
            "Epoch 93/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15253097.7812 - mae: 2769.5332 - val_loss: 5207815.0000 - val_mae: 1978.4860\n",
            "Epoch 94/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22670495.5938 - mae: 2958.1682 - val_loss: 5481308.0000 - val_mae: 2065.0061\n",
            "Epoch 95/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13649634.3125 - mae: 2547.6898 - val_loss: 4676677.5000 - val_mae: 1834.7715\n",
            "Epoch 96/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27343076.8750 - mae: 3894.5519 - val_loss: 5070637.0000 - val_mae: 1942.6027\n",
            "Epoch 97/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21902104.0625 - mae: 3503.4805 - val_loss: 5018396.0000 - val_mae: 1908.6400\n",
            "Epoch 98/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16555185.8750 - mae: 3005.3522 - val_loss: 5512505.5000 - val_mae: 2057.9460\n",
            "Epoch 99/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13435093.4375 - mae: 2692.8034 - val_loss: 5332262.5000 - val_mae: 2018.1381\n",
            "Epoch 100/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 14086759.3750 - mae: 2473.8038 - val_loss: 5000553.5000 - val_mae: 1929.6583\n",
            "processing fold # 2\n",
            "Epoch 1/100\n",
            "15/15 [==============================] - 1s 19ms/step - loss: 259594989.0000 - mae: 13527.9876 - val_loss: 435828032.0000 - val_mae: 17673.8301\n",
            "Epoch 2/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 251440294.0000 - mae: 13566.2302 - val_loss: 432480736.0000 - val_mae: 17583.0996\n",
            "Epoch 3/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 231934970.0000 - mae: 12783.6078 - val_loss: 424541888.0000 - val_mae: 17373.1055\n",
            "Epoch 4/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 217373732.0000 - mae: 12603.9559 - val_loss: 410276768.0000 - val_mae: 16991.8594\n",
            "Epoch 5/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 208033756.0000 - mae: 12205.6385 - val_loss: 388106048.0000 - val_mae: 16398.6934\n",
            "Epoch 6/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 182850552.0000 - mae: 11117.6294 - val_loss: 358262528.0000 - val_mae: 15572.6416\n",
            "Epoch 7/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 166909043.0000 - mae: 10685.3673 - val_loss: 321381440.0000 - val_mae: 14503.1631\n",
            "Epoch 8/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 151878887.0000 - mae: 9766.2632 - val_loss: 275754912.0000 - val_mae: 13086.0293\n",
            "Epoch 9/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 108351206.0000 - mae: 7771.5650 - val_loss: 228466656.0000 - val_mae: 11463.2256\n",
            "Epoch 10/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 108274068.2500 - mae: 7450.8614 - val_loss: 185532432.0000 - val_mae: 9795.9902\n",
            "Epoch 11/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 64937386.5000 - mae: 5267.3052 - val_loss: 141531056.0000 - val_mae: 7986.9844\n",
            "Epoch 12/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 35412777.8750 - mae: 3590.9436 - val_loss: 105299608.0000 - val_mae: 6786.8306\n",
            "Epoch 13/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 29506576.0000 - mae: 3635.9431 - val_loss: 80871688.0000 - val_mae: 6153.0981\n",
            "Epoch 14/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 38024516.5000 - mae: 4355.5307 - val_loss: 68675096.0000 - val_mae: 5694.2983\n",
            "Epoch 15/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 29107737.7500 - mae: 3702.0119 - val_loss: 60809972.0000 - val_mae: 5388.8135\n",
            "Epoch 16/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 28269606.6250 - mae: 3607.6475 - val_loss: 57930656.0000 - val_mae: 5259.0029\n",
            "Epoch 17/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 31050676.6250 - mae: 3745.6240 - val_loss: 56169716.0000 - val_mae: 5151.3618\n",
            "Epoch 18/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26310376.1250 - mae: 3677.0780 - val_loss: 46103636.0000 - val_mae: 4747.8091\n",
            "Epoch 19/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 37672571.6250 - mae: 4074.2714 - val_loss: 43570204.0000 - val_mae: 4622.4575\n",
            "Epoch 20/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22795707.5625 - mae: 3096.7449 - val_loss: 38330372.0000 - val_mae: 4406.8384\n",
            "Epoch 21/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24594104.6875 - mae: 3310.1268 - val_loss: 45484768.0000 - val_mae: 4637.8955\n",
            "Epoch 22/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 20268465.5625 - mae: 3460.5828 - val_loss: 37558836.0000 - val_mae: 4293.2861\n",
            "Epoch 23/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22095638.6250 - mae: 3490.2875 - val_loss: 38449892.0000 - val_mae: 4303.2202\n",
            "Epoch 24/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 17884791.2500 - mae: 3023.7731 - val_loss: 42259988.0000 - val_mae: 4461.4038\n",
            "Epoch 25/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 33845971.0000 - mae: 3555.0159 - val_loss: 45891076.0000 - val_mae: 4578.5674\n",
            "Epoch 26/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 24667914.8750 - mae: 3463.6987 - val_loss: 45657544.0000 - val_mae: 4540.6880\n",
            "Epoch 27/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27179753.1875 - mae: 3505.6824 - val_loss: 44350560.0000 - val_mae: 4451.9526\n",
            "Epoch 28/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 20367927.7812 - mae: 2955.2231 - val_loss: 40996456.0000 - val_mae: 4268.7964\n",
            "Epoch 29/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27442221.1562 - mae: 3033.6488 - val_loss: 40614656.0000 - val_mae: 4241.0518\n",
            "Epoch 30/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19301887.5469 - mae: 2981.7847 - val_loss: 34898412.0000 - val_mae: 3979.5337\n",
            "Epoch 31/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 12471413.5625 - mae: 2674.3648 - val_loss: 37258092.0000 - val_mae: 4098.7153\n",
            "Epoch 32/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 28671259.3750 - mae: 3772.1102 - val_loss: 41486140.0000 - val_mae: 4347.4971\n",
            "Epoch 33/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18199677.1250 - mae: 2913.6687 - val_loss: 39508276.0000 - val_mae: 4299.9927\n",
            "Epoch 34/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26663206.5000 - mae: 3710.5722 - val_loss: 34472988.0000 - val_mae: 4005.6626\n",
            "Epoch 35/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14278250.3750 - mae: 2892.3877 - val_loss: 32033478.0000 - val_mae: 3805.4573\n",
            "Epoch 36/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14458111.3750 - mae: 2859.8223 - val_loss: 33463260.0000 - val_mae: 3873.0168\n",
            "Epoch 37/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17061842.0625 - mae: 3024.5049 - val_loss: 31892374.0000 - val_mae: 3818.6580\n",
            "Epoch 38/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21692322.3750 - mae: 3002.9305 - val_loss: 39029504.0000 - val_mae: 4265.4302\n",
            "Epoch 39/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 28508852.1250 - mae: 3331.3019 - val_loss: 34655988.0000 - val_mae: 3993.2871\n",
            "Epoch 40/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13215357.4062 - mae: 2644.7198 - val_loss: 36425400.0000 - val_mae: 4104.8892\n",
            "Epoch 41/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 14751190.6094 - mae: 2480.6487 - val_loss: 40721924.0000 - val_mae: 4340.0752\n",
            "Epoch 42/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24245973.7500 - mae: 3141.9225 - val_loss: 29475754.0000 - val_mae: 3713.6990\n",
            "Epoch 43/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19506632.8125 - mae: 2986.5598 - val_loss: 37507336.0000 - val_mae: 4180.8433\n",
            "Epoch 44/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 9605484.5312 - mae: 2327.6749 - val_loss: 33363598.0000 - val_mae: 3942.2427\n",
            "Epoch 45/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18616301.1250 - mae: 3044.7329 - val_loss: 34676072.0000 - val_mae: 4015.9036\n",
            "Epoch 46/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18412128.1875 - mae: 3075.7384 - val_loss: 44055392.0000 - val_mae: 4639.7871\n",
            "Epoch 47/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15876139.6250 - mae: 2835.3340 - val_loss: 36755696.0000 - val_mae: 4219.9248\n",
            "Epoch 48/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20685793.5625 - mae: 3057.7551 - val_loss: 33836500.0000 - val_mae: 4007.1274\n",
            "Epoch 49/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14472588.8750 - mae: 2917.3946 - val_loss: 26975646.0000 - val_mae: 3549.2283\n",
            "Epoch 50/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14946473.8125 - mae: 2810.1001 - val_loss: 29047458.0000 - val_mae: 3725.3464\n",
            "Epoch 51/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14867155.7188 - mae: 2673.7531 - val_loss: 36995116.0000 - val_mae: 4329.3770\n",
            "Epoch 52/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 16363012.9375 - mae: 2700.6046 - val_loss: 35241240.0000 - val_mae: 4170.2046\n",
            "Epoch 53/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 13187463.0938 - mae: 2234.9167 - val_loss: 30529494.0000 - val_mae: 3844.1716\n",
            "Epoch 54/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14330300.3438 - mae: 2604.8153 - val_loss: 30345664.0000 - val_mae: 3800.3516\n",
            "Epoch 55/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16789038.6250 - mae: 3130.5458 - val_loss: 28554878.0000 - val_mae: 3701.3418\n",
            "Epoch 56/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 18464227.5000 - mae: 2959.0318 - val_loss: 35345320.0000 - val_mae: 4154.5205\n",
            "Epoch 57/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 12426320.4688 - mae: 2543.6532 - val_loss: 37917628.0000 - val_mae: 4346.4341\n",
            "Epoch 58/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 23403055.5000 - mae: 3383.0894 - val_loss: 34589032.0000 - val_mae: 4156.7993\n",
            "Epoch 59/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14612663.0625 - mae: 2645.2086 - val_loss: 34300420.0000 - val_mae: 4115.3564\n",
            "Epoch 60/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 11543377.8125 - mae: 2467.1594 - val_loss: 32930892.0000 - val_mae: 4049.0574\n",
            "Epoch 61/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16023459.2812 - mae: 2754.3911 - val_loss: 29935692.0000 - val_mae: 3829.4897\n",
            "Epoch 62/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22223348.0000 - mae: 3418.5537 - val_loss: 31494004.0000 - val_mae: 3921.3257\n",
            "Epoch 63/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12021471.8594 - mae: 2470.3294 - val_loss: 30363582.0000 - val_mae: 3827.7463\n",
            "Epoch 64/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12898280.5938 - mae: 2433.8152 - val_loss: 23943052.0000 - val_mae: 3413.0242\n",
            "Epoch 65/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15298166.5312 - mae: 2725.0176 - val_loss: 25355174.0000 - val_mae: 3508.2810\n",
            "Epoch 66/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20792398.5625 - mae: 3093.0452 - val_loss: 24336946.0000 - val_mae: 3431.4067\n",
            "Epoch 67/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17555874.6250 - mae: 3057.7280 - val_loss: 29040684.0000 - val_mae: 3806.7910\n",
            "Epoch 68/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18385092.9375 - mae: 3057.2358 - val_loss: 29309584.0000 - val_mae: 3824.5190\n",
            "Epoch 69/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15848335.7500 - mae: 2690.2131 - val_loss: 30408074.0000 - val_mae: 3922.9177\n",
            "Epoch 70/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11710545.0625 - mae: 2535.0626 - val_loss: 28795034.0000 - val_mae: 3796.1597\n",
            "Epoch 71/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 8249762.4062 - mae: 1924.3964 - val_loss: 24503554.0000 - val_mae: 3505.6289\n",
            "Epoch 72/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14199484.6562 - mae: 2409.8147 - val_loss: 19561950.0000 - val_mae: 3139.4175\n",
            "Epoch 73/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 18885966.6250 - mae: 2705.9842 - val_loss: 19079066.0000 - val_mae: 3093.1877\n",
            "Epoch 74/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 20663186.0000 - mae: 3348.2719 - val_loss: 31224800.0000 - val_mae: 4040.8655\n",
            "Epoch 75/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15904576.5625 - mae: 2632.9601 - val_loss: 24103842.0000 - val_mae: 3494.3469\n",
            "Epoch 76/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18796114.9375 - mae: 3107.7604 - val_loss: 24617204.0000 - val_mae: 3608.5774\n",
            "Epoch 77/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10620551.0781 - mae: 2336.0425 - val_loss: 28602276.0000 - val_mae: 3922.3794\n",
            "Epoch 78/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18860820.3125 - mae: 2957.0361 - val_loss: 28167106.0000 - val_mae: 3790.9734\n",
            "Epoch 79/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17163659.8750 - mae: 2861.6819 - val_loss: 34062944.0000 - val_mae: 4203.3740\n",
            "Epoch 80/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14853096.7500 - mae: 2903.3292 - val_loss: 29037100.0000 - val_mae: 3831.1067\n",
            "Epoch 81/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12953627.2188 - mae: 2428.6199 - val_loss: 26555446.0000 - val_mae: 3601.4548\n",
            "Epoch 82/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16012855.5000 - mae: 2827.9843 - val_loss: 27237486.0000 - val_mae: 3688.0842\n",
            "Epoch 83/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16826028.6875 - mae: 3005.1595 - val_loss: 26369302.0000 - val_mae: 3684.7271\n",
            "Epoch 84/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 21509807.7500 - mae: 3287.6361 - val_loss: 24207648.0000 - val_mae: 3539.4841\n",
            "Epoch 85/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16934307.0781 - mae: 2730.6421 - val_loss: 24937302.0000 - val_mae: 3574.6274\n",
            "Epoch 86/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12830601.2109 - mae: 2446.7282 - val_loss: 24739708.0000 - val_mae: 3482.7480\n",
            "Epoch 87/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20027628.0000 - mae: 3192.9754 - val_loss: 25461614.0000 - val_mae: 3576.3752\n",
            "Epoch 88/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20034183.3125 - mae: 2902.7456 - val_loss: 27422876.0000 - val_mae: 3807.2449\n",
            "Epoch 89/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10914466.0000 - mae: 2323.3550 - val_loss: 22655742.0000 - val_mae: 3367.5569\n",
            "Epoch 90/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13299875.1875 - mae: 2559.4876 - val_loss: 32165654.0000 - val_mae: 4212.0356\n",
            "Epoch 91/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15516345.8125 - mae: 2733.6682 - val_loss: 33067628.0000 - val_mae: 4188.8818\n",
            "Epoch 92/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 13282264.0000 - mae: 2409.2119 - val_loss: 31151022.0000 - val_mae: 3991.9629\n",
            "Epoch 93/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13180659.0625 - mae: 2640.2628 - val_loss: 28242372.0000 - val_mae: 3752.1731\n",
            "Epoch 94/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16797540.4375 - mae: 2774.2412 - val_loss: 29614174.0000 - val_mae: 3875.0652\n",
            "Epoch 95/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14038045.8750 - mae: 2612.1457 - val_loss: 29066388.0000 - val_mae: 3788.1707\n",
            "Epoch 96/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15645421.9375 - mae: 2894.5967 - val_loss: 32780938.0000 - val_mae: 4053.5388\n",
            "Epoch 97/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17508609.6875 - mae: 2855.7041 - val_loss: 36922824.0000 - val_mae: 4387.4761\n",
            "Epoch 98/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11146050.8438 - mae: 2372.1908 - val_loss: 38771684.0000 - val_mae: 4538.1631\n",
            "Epoch 99/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 13509080.2500 - mae: 2688.2231 - val_loss: 38087712.0000 - val_mae: 4488.4155\n",
            "Epoch 100/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13186640.2188 - mae: 2520.3261 - val_loss: 42561176.0000 - val_mae: 4788.5352\n",
            "processing fold # 3\n",
            "Epoch 1/100\n",
            "15/15 [==============================] - 1s 16ms/step - loss: 263001869.0000 - mae: 13777.4525 - val_loss: 131531608.0000 - val_mae: 10787.3506\n",
            "Epoch 2/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 348418258.0000 - mae: 15575.6218 - val_loss: 129779904.0000 - val_mae: 10709.4346\n",
            "Epoch 3/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 336978562.0000 - mae: 15414.0424 - val_loss: 125495184.0000 - val_mae: 10521.6143\n",
            "Epoch 4/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 266290254.0000 - mae: 13487.3031 - val_loss: 118667968.0000 - val_mae: 10213.8730\n",
            "Epoch 5/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 276992002.0000 - mae: 13410.6559 - val_loss: 108048448.0000 - val_mae: 9722.1182\n",
            "Epoch 6/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 276807837.0000 - mae: 13713.1210 - val_loss: 93735216.0000 - val_mae: 9024.8936\n",
            "Epoch 7/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 246291354.0000 - mae: 12683.8928 - val_loss: 76268440.0000 - val_mae: 8095.0835\n",
            "Epoch 8/100\n",
            "15/15 [==============================] - 0s 9ms/step - loss: 206002921.0000 - mae: 11547.5081 - val_loss: 56511196.0000 - val_mae: 6900.4341\n",
            "Epoch 9/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 163899559.7500 - mae: 9766.5853 - val_loss: 35216324.0000 - val_mae: 5329.4370\n",
            "Epoch 10/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 114641588.0000 - mae: 7875.3008 - val_loss: 17394552.0000 - val_mae: 3502.1987\n",
            "Epoch 11/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 88779518.0000 - mae: 6411.2835 - val_loss: 7818205.0000 - val_mae: 2085.9209\n",
            "Epoch 12/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 86305682.0000 - mae: 6048.5473 - val_loss: 4885064.0000 - val_mae: 1717.3185\n",
            "Epoch 13/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 67195435.5000 - mae: 5667.2132 - val_loss: 7445637.0000 - val_mae: 2252.6292\n",
            "Epoch 14/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 33208580.3125 - mae: 4008.1387 - val_loss: 10225235.0000 - val_mae: 2533.2974\n",
            "Epoch 15/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 32217074.6250 - mae: 3648.9058 - val_loss: 17250118.0000 - val_mae: 3290.7947\n",
            "Epoch 16/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25635330.5938 - mae: 3168.8771 - val_loss: 16699623.0000 - val_mae: 3293.3503\n",
            "Epoch 17/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 42665495.5625 - mae: 4217.3262 - val_loss: 16580185.0000 - val_mae: 3323.4231\n",
            "Epoch 18/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 37512717.8750 - mae: 4430.9704 - val_loss: 16759456.0000 - val_mae: 3374.6160\n",
            "Epoch 19/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23874158.0625 - mae: 3571.4459 - val_loss: 18195238.0000 - val_mae: 3523.1372\n",
            "Epoch 20/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 32146071.1250 - mae: 3894.9848 - val_loss: 17353870.0000 - val_mae: 3474.1868\n",
            "Epoch 21/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 31180970.5000 - mae: 3929.9037 - val_loss: 21632740.0000 - val_mae: 3842.7793\n",
            "Epoch 22/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 18908649.5000 - mae: 3399.7572 - val_loss: 17733410.0000 - val_mae: 3468.2097\n",
            "Epoch 23/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20141505.0000 - mae: 3042.1742 - val_loss: 19249408.0000 - val_mae: 3616.4336\n",
            "Epoch 24/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22562612.1250 - mae: 3589.6600 - val_loss: 17959724.0000 - val_mae: 3457.8547\n",
            "Epoch 25/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24181894.8125 - mae: 3576.9924 - val_loss: 17617386.0000 - val_mae: 3409.0886\n",
            "Epoch 26/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 29390596.3750 - mae: 3943.4536 - val_loss: 26548800.0000 - val_mae: 4141.8281\n",
            "Epoch 27/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18715906.7500 - mae: 3317.0433 - val_loss: 16720063.0000 - val_mae: 3299.7708\n",
            "Epoch 28/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27853037.8750 - mae: 3658.4941 - val_loss: 14699143.0000 - val_mae: 3072.7161\n",
            "Epoch 29/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25069135.0000 - mae: 3475.8884 - val_loss: 15768461.0000 - val_mae: 3169.0176\n",
            "Epoch 30/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26375977.1875 - mae: 3487.3833 - val_loss: 15432698.0000 - val_mae: 3133.7122\n",
            "Epoch 31/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26514994.8750 - mae: 3603.9081 - val_loss: 16583446.0000 - val_mae: 3227.0325\n",
            "Epoch 32/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27278280.5000 - mae: 3499.8568 - val_loss: 20428062.0000 - val_mae: 3526.7896\n",
            "Epoch 33/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22270421.3750 - mae: 3300.5330 - val_loss: 17966746.0000 - val_mae: 3305.1516\n",
            "Epoch 34/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 28215684.4375 - mae: 3667.7554 - val_loss: 18256370.0000 - val_mae: 3329.7583\n",
            "Epoch 35/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 23302033.7500 - mae: 3403.9270 - val_loss: 18327734.0000 - val_mae: 3331.7812\n",
            "Epoch 36/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23033125.1875 - mae: 3147.6846 - val_loss: 14780923.0000 - val_mae: 3045.2363\n",
            "Epoch 37/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25456017.0000 - mae: 3181.4847 - val_loss: 15297742.0000 - val_mae: 3074.8083\n",
            "Epoch 38/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 14234681.8750 - mae: 2743.6095 - val_loss: 14620433.0000 - val_mae: 2947.3469\n",
            "Epoch 39/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19133438.7500 - mae: 3233.1379 - val_loss: 13035962.0000 - val_mae: 2822.6348\n",
            "Epoch 40/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 46305889.5000 - mae: 4021.4492 - val_loss: 14520009.0000 - val_mae: 2935.5559\n",
            "Epoch 41/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19305828.0000 - mae: 3023.8776 - val_loss: 16679009.0000 - val_mae: 3111.8811\n",
            "Epoch 42/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 19384609.3750 - mae: 2935.3772 - val_loss: 24896850.0000 - val_mae: 3695.6711\n",
            "Epoch 43/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20639268.7500 - mae: 3410.8411 - val_loss: 17558610.0000 - val_mae: 3142.7036\n",
            "Epoch 44/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23294979.1250 - mae: 3528.6777 - val_loss: 15659554.0000 - val_mae: 3045.5735\n",
            "Epoch 45/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14536497.0625 - mae: 2689.8569 - val_loss: 21924720.0000 - val_mae: 3449.5591\n",
            "Epoch 46/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 31273525.0000 - mae: 3834.1360 - val_loss: 16645192.0000 - val_mae: 3076.4487\n",
            "Epoch 47/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23494442.0000 - mae: 3341.9265 - val_loss: 17599274.0000 - val_mae: 3176.2488\n",
            "Epoch 48/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20634906.6250 - mae: 3090.1097 - val_loss: 20302886.0000 - val_mae: 3399.0425\n",
            "Epoch 49/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12297003.2500 - mae: 2657.3834 - val_loss: 15345789.0000 - val_mae: 2990.3638\n",
            "Epoch 50/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 16359324.1250 - mae: 2822.0648 - val_loss: 19327356.0000 - val_mae: 3239.0168\n",
            "Epoch 51/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14041544.8438 - mae: 2651.7258 - val_loss: 14464710.0000 - val_mae: 2872.9001\n",
            "Epoch 52/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16984905.3125 - mae: 3103.6073 - val_loss: 15966746.0000 - val_mae: 3018.0330\n",
            "Epoch 53/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 25162720.2500 - mae: 3233.2574 - val_loss: 20195968.0000 - val_mae: 3347.0247\n",
            "Epoch 54/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26161943.8750 - mae: 3438.2504 - val_loss: 17153872.0000 - val_mae: 3094.5916\n",
            "Epoch 55/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15178080.6250 - mae: 2703.6409 - val_loss: 15213433.0000 - val_mae: 2963.6265\n",
            "Epoch 56/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12423785.8750 - mae: 2537.2455 - val_loss: 15202478.0000 - val_mae: 2878.2180\n",
            "Epoch 57/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23894720.2500 - mae: 3211.4937 - val_loss: 14232299.0000 - val_mae: 2809.4666\n",
            "Epoch 58/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21768926.9375 - mae: 3310.6176 - val_loss: 16213744.0000 - val_mae: 2920.5549\n",
            "Epoch 59/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 15362122.1250 - mae: 2815.8069 - val_loss: 21337456.0000 - val_mae: 3315.6648\n",
            "Epoch 60/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 11227844.0156 - mae: 2343.6409 - val_loss: 19128668.0000 - val_mae: 3211.3345\n",
            "Epoch 61/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12812483.7500 - mae: 2636.7730 - val_loss: 19975300.0000 - val_mae: 3229.8767\n",
            "Epoch 62/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20672035.6250 - mae: 3165.8027 - val_loss: 18303762.0000 - val_mae: 3116.3640\n",
            "Epoch 63/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14923827.6875 - mae: 2750.9884 - val_loss: 19779970.0000 - val_mae: 3214.0386\n",
            "Epoch 64/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18413304.9375 - mae: 3001.0712 - val_loss: 18828586.0000 - val_mae: 3096.9905\n",
            "Epoch 65/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27248396.1250 - mae: 3556.6322 - val_loss: 18187636.0000 - val_mae: 3084.1018\n",
            "Epoch 66/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24415043.2500 - mae: 3455.4693 - val_loss: 17308238.0000 - val_mae: 2995.0476\n",
            "Epoch 67/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15560102.3750 - mae: 2703.9597 - val_loss: 15172951.0000 - val_mae: 2843.7556\n",
            "Epoch 68/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 14854467.0938 - mae: 2593.7229 - val_loss: 22782308.0000 - val_mae: 3404.0032\n",
            "Epoch 69/100\n",
            "15/15 [==============================] - 0s 9ms/step - loss: 35327609.8750 - mae: 3712.7966 - val_loss: 15496784.0000 - val_mae: 2923.6562\n",
            "Epoch 70/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22850326.5625 - mae: 3433.1488 - val_loss: 16933736.0000 - val_mae: 2982.8013\n",
            "Epoch 71/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16422388.9375 - mae: 2868.8404 - val_loss: 20379498.0000 - val_mae: 3210.1165\n",
            "Epoch 72/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26158682.3750 - mae: 3614.1381 - val_loss: 17277406.0000 - val_mae: 3012.8118\n",
            "Epoch 73/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 21656777.1250 - mae: 3276.4707 - val_loss: 15828526.0000 - val_mae: 2913.7595\n",
            "Epoch 74/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21491191.2500 - mae: 3214.6975 - val_loss: 13531077.0000 - val_mae: 2692.1909\n",
            "Epoch 75/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 14501415.9375 - mae: 2811.7459 - val_loss: 14392639.0000 - val_mae: 2761.7144\n",
            "Epoch 76/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23274541.0000 - mae: 3037.0654 - val_loss: 17054740.0000 - val_mae: 2978.3784\n",
            "Epoch 77/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 31562406.3750 - mae: 3805.9452 - val_loss: 17953178.0000 - val_mae: 3021.6929\n",
            "Epoch 78/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17578341.0000 - mae: 3046.8451 - val_loss: 16370662.0000 - val_mae: 2901.5972\n",
            "Epoch 79/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20267047.0625 - mae: 2871.9768 - val_loss: 18737416.0000 - val_mae: 3093.9497\n",
            "Epoch 80/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 18848290.3125 - mae: 2900.5151 - val_loss: 13609843.0000 - val_mae: 2693.7192\n",
            "Epoch 81/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 17697451.5000 - mae: 2912.2622 - val_loss: 15363298.0000 - val_mae: 2854.8191\n",
            "Epoch 82/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10386342.5938 - mae: 2316.4096 - val_loss: 15178290.0000 - val_mae: 2775.8801\n",
            "Epoch 83/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 33181228.2812 - mae: 3388.4602 - val_loss: 17913380.0000 - val_mae: 3016.0613\n",
            "Epoch 84/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10858327.2031 - mae: 2311.6509 - val_loss: 12863535.0000 - val_mae: 2658.4397\n",
            "Epoch 85/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17856375.3750 - mae: 2668.3056 - val_loss: 14152499.0000 - val_mae: 2759.4709\n",
            "Epoch 86/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12495512.6875 - mae: 2639.7025 - val_loss: 14980808.0000 - val_mae: 2747.3379\n",
            "Epoch 87/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10719803.9688 - mae: 2278.1699 - val_loss: 14791278.0000 - val_mae: 2728.4429\n",
            "Epoch 88/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14162259.4688 - mae: 2610.3025 - val_loss: 10688681.0000 - val_mae: 2403.5281\n",
            "Epoch 89/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 11306932.0625 - mae: 2386.9823 - val_loss: 13993645.0000 - val_mae: 2619.8906\n",
            "Epoch 90/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17351276.7500 - mae: 2763.1278 - val_loss: 21470246.0000 - val_mae: 3272.5854\n",
            "Epoch 91/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 21843128.3125 - mae: 3422.2789 - val_loss: 18970636.0000 - val_mae: 3141.0044\n",
            "Epoch 92/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11826332.5625 - mae: 2568.5783 - val_loss: 15429566.0000 - val_mae: 2827.3438\n",
            "Epoch 93/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13294961.9531 - mae: 2596.0299 - val_loss: 15964030.0000 - val_mae: 2812.1287\n",
            "Epoch 94/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23402694.0625 - mae: 3047.7444 - val_loss: 15744406.0000 - val_mae: 2800.7000\n",
            "Epoch 95/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13782255.4375 - mae: 2620.9197 - val_loss: 15418943.0000 - val_mae: 2780.4062\n",
            "Epoch 96/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13443380.0625 - mae: 2808.5970 - val_loss: 23119422.0000 - val_mae: 3349.9419\n",
            "Epoch 97/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25573300.7500 - mae: 3372.6259 - val_loss: 17494236.0000 - val_mae: 2982.5417\n",
            "Epoch 98/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 13815026.4062 - mae: 2621.3901 - val_loss: 16254570.0000 - val_mae: 2895.6245\n",
            "Epoch 99/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14641240.7734 - mae: 2506.0178 - val_loss: 19023980.0000 - val_mae: 3077.9363\n",
            "Epoch 100/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17486658.6250 - mae: 3042.2363 - val_loss: 16577914.0000 - val_mae: 2899.6956\n",
            "processing fold # 4\n",
            "Epoch 1/100\n",
            "15/15 [==============================] - 1s 17ms/step - loss: 274667445.0000 - mae: 13429.4048 - val_loss: 321207904.0000 - val_mae: 15652.3613\n",
            "Epoch 2/100\n",
            "15/15 [==============================] - 0s 8ms/step - loss: 304040167.0000 - mae: 14457.6448 - val_loss: 319028512.0000 - val_mae: 15581.4189\n",
            "Epoch 3/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 241955241.0000 - mae: 13150.1163 - val_loss: 313772224.0000 - val_mae: 15412.2490\n",
            "Epoch 4/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 226387348.0000 - mae: 12538.4915 - val_loss: 305327136.0000 - val_mae: 15135.4785\n",
            "Epoch 5/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 276821131.0000 - mae: 13609.2134 - val_loss: 292931744.0000 - val_mae: 14722.5938\n",
            "Epoch 6/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 200291597.5000 - mae: 11693.2068 - val_loss: 273284640.0000 - val_mae: 14054.7266\n",
            "Epoch 7/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 241664585.0000 - mae: 12558.6348 - val_loss: 253686944.0000 - val_mae: 13346.6221\n",
            "Epoch 8/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 175043933.0000 - mae: 10211.9048 - val_loss: 224347632.0000 - val_mae: 12231.2002\n",
            "Epoch 9/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 155298173.0000 - mae: 9859.4705 - val_loss: 192372528.0000 - val_mae: 10889.9150\n",
            "Epoch 10/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 128014277.2500 - mae: 8497.8705 - val_loss: 158451536.0000 - val_mae: 9291.6650\n",
            "Epoch 11/100\n",
            "15/15 [==============================] - 0s 8ms/step - loss: 88482857.2500 - mae: 6874.1386 - val_loss: 124992008.0000 - val_mae: 7429.8940\n",
            "Epoch 12/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 63122519.3750 - mae: 4707.4584 - val_loss: 101155304.0000 - val_mae: 6132.8101\n",
            "Epoch 13/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 66142457.7500 - mae: 5459.8947 - val_loss: 84044376.0000 - val_mae: 5297.8511\n",
            "Epoch 14/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 47861916.2500 - mae: 4399.2022 - val_loss: 73463016.0000 - val_mae: 4822.0977\n",
            "Epoch 15/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 35270665.6250 - mae: 3938.4831 - val_loss: 65507012.0000 - val_mae: 4632.6206\n",
            "Epoch 16/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25290552.2500 - mae: 3437.8053 - val_loss: 61930524.0000 - val_mae: 4556.5400\n",
            "Epoch 17/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 21008722.1875 - mae: 3159.1542 - val_loss: 60488136.0000 - val_mae: 4505.6665\n",
            "Epoch 18/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 29762245.8750 - mae: 3857.3932 - val_loss: 60669640.0000 - val_mae: 4497.2402\n",
            "Epoch 19/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18368979.4375 - mae: 3151.2209 - val_loss: 55858712.0000 - val_mae: 4399.5347\n",
            "Epoch 20/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 29107893.5625 - mae: 3833.7246 - val_loss: 53923832.0000 - val_mae: 4357.8843\n",
            "Epoch 21/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24294306.3750 - mae: 3517.5234 - val_loss: 54544500.0000 - val_mae: 4312.3364\n",
            "Epoch 22/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23524368.3125 - mae: 3729.5761 - val_loss: 50787048.0000 - val_mae: 4228.6689\n",
            "Epoch 23/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22763748.7500 - mae: 3450.4209 - val_loss: 48137028.0000 - val_mae: 4131.0161\n",
            "Epoch 24/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 21652555.6875 - mae: 3367.9367 - val_loss: 48011420.0000 - val_mae: 4169.8037\n",
            "Epoch 25/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 20654352.8750 - mae: 3192.8928 - val_loss: 46610244.0000 - val_mae: 4107.4541\n",
            "Epoch 26/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 25108836.9375 - mae: 3530.5349 - val_loss: 49278644.0000 - val_mae: 4083.0532\n",
            "Epoch 27/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25744534.6250 - mae: 3532.0679 - val_loss: 47566756.0000 - val_mae: 4014.1548\n",
            "Epoch 28/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 19161198.2969 - mae: 2938.6270 - val_loss: 45550664.0000 - val_mae: 3936.7336\n",
            "Epoch 29/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27410714.2500 - mae: 3303.2101 - val_loss: 43768916.0000 - val_mae: 3875.3179\n",
            "Epoch 30/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25791142.3750 - mae: 3630.6763 - val_loss: 43479488.0000 - val_mae: 3879.4585\n",
            "Epoch 31/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22303068.1562 - mae: 3205.2158 - val_loss: 43170908.0000 - val_mae: 3808.6426\n",
            "Epoch 32/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25329044.8750 - mae: 3194.8346 - val_loss: 40337908.0000 - val_mae: 3710.5825\n",
            "Epoch 33/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25167151.6250 - mae: 3450.9385 - val_loss: 42523452.0000 - val_mae: 3757.7031\n",
            "Epoch 34/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 31128542.5625 - mae: 3378.0963 - val_loss: 43708484.0000 - val_mae: 3765.5613\n",
            "Epoch 35/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15251730.0625 - mae: 2791.1135 - val_loss: 41275672.0000 - val_mae: 3637.0200\n",
            "Epoch 36/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13071823.6875 - mae: 2589.2674 - val_loss: 37925532.0000 - val_mae: 3581.3474\n",
            "Epoch 37/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24304545.0000 - mae: 3240.8768 - val_loss: 41417148.0000 - val_mae: 3613.1394\n",
            "Epoch 38/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 32546882.7500 - mae: 3745.6178 - val_loss: 44115292.0000 - val_mae: 3693.7617\n",
            "Epoch 39/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14570445.2188 - mae: 2506.4715 - val_loss: 39636856.0000 - val_mae: 3509.6362\n",
            "Epoch 40/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 29037672.7500 - mae: 3450.7331 - val_loss: 38053456.0000 - val_mae: 3477.9375\n",
            "Epoch 41/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12879573.5625 - mae: 2680.0291 - val_loss: 36762980.0000 - val_mae: 3460.3296\n",
            "Epoch 42/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20475652.7500 - mae: 3168.1232 - val_loss: 35539060.0000 - val_mae: 3444.7144\n",
            "Epoch 43/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 21609652.2500 - mae: 3233.9823 - val_loss: 35488488.0000 - val_mae: 3329.8279\n",
            "Epoch 44/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 20900842.9375 - mae: 2968.9197 - val_loss: 36281768.0000 - val_mae: 3388.6211\n",
            "Epoch 45/100\n",
            "15/15 [==============================] - 0s 8ms/step - loss: 13232694.5625 - mae: 2737.6506 - val_loss: 37390044.0000 - val_mae: 3467.2344\n",
            "Epoch 46/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26807424.8750 - mae: 3065.7460 - val_loss: 36353108.0000 - val_mae: 3355.1467\n",
            "Epoch 47/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17371416.3750 - mae: 2926.8271 - val_loss: 34635256.0000 - val_mae: 3286.6931\n",
            "Epoch 48/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 17596321.1875 - mae: 2987.3837 - val_loss: 31396350.0000 - val_mae: 3134.9509\n",
            "Epoch 49/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 23541129.7500 - mae: 3309.5658 - val_loss: 33900564.0000 - val_mae: 3309.0881\n",
            "Epoch 50/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11014915.2188 - mae: 2361.8164 - val_loss: 30046578.0000 - val_mae: 3099.2852\n",
            "Epoch 51/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13104674.5000 - mae: 2662.2350 - val_loss: 32774716.0000 - val_mae: 3274.0764\n",
            "Epoch 52/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18793762.3594 - mae: 2821.2286 - val_loss: 31632336.0000 - val_mae: 3227.1975\n",
            "Epoch 53/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 24582919.5000 - mae: 3625.2643 - val_loss: 34771984.0000 - val_mae: 3479.4302\n",
            "Epoch 54/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 25418100.1875 - mae: 3161.1153 - val_loss: 30711402.0000 - val_mae: 3200.4692\n",
            "Epoch 55/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15808183.8281 - mae: 2744.4733 - val_loss: 28495388.0000 - val_mae: 3006.2048\n",
            "Epoch 56/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18417659.8750 - mae: 3095.2319 - val_loss: 32556796.0000 - val_mae: 3369.1897\n",
            "Epoch 57/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13466874.7500 - mae: 2673.5783 - val_loss: 34929032.0000 - val_mae: 3538.4377\n",
            "Epoch 58/100\n",
            "15/15 [==============================] - 0s 8ms/step - loss: 16299673.7500 - mae: 2795.3431 - val_loss: 34537384.0000 - val_mae: 3466.0408\n",
            "Epoch 59/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17513150.1875 - mae: 2691.1213 - val_loss: 32690774.0000 - val_mae: 3312.1321\n",
            "Epoch 60/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12019273.9375 - mae: 2570.5515 - val_loss: 32362466.0000 - val_mae: 3341.7617\n",
            "Epoch 61/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19938695.9375 - mae: 2987.0400 - val_loss: 27566186.0000 - val_mae: 2945.3269\n",
            "Epoch 62/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13715401.1875 - mae: 2907.5904 - val_loss: 33025924.0000 - val_mae: 3435.0071\n",
            "Epoch 63/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20371240.3125 - mae: 2961.0571 - val_loss: 35744948.0000 - val_mae: 3640.1716\n",
            "Epoch 64/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 13555811.8438 - mae: 2273.3967 - val_loss: 30574852.0000 - val_mae: 3222.7676\n",
            "Epoch 65/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13562524.6250 - mae: 2791.7230 - val_loss: 32020284.0000 - val_mae: 3368.7915\n",
            "Epoch 66/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15545985.0625 - mae: 2664.1530 - val_loss: 30594246.0000 - val_mae: 3269.1406\n",
            "Epoch 67/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 10320353.6250 - mae: 2288.9182 - val_loss: 34009436.0000 - val_mae: 3601.9409\n",
            "Epoch 68/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18247041.2500 - mae: 2991.2168 - val_loss: 35067096.0000 - val_mae: 3637.4575\n",
            "Epoch 69/100\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 16004172.2812 - mae: 2952.8967 - val_loss: 27681760.0000 - val_mae: 3059.2595\n",
            "Epoch 70/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18885857.8125 - mae: 2974.6844 - val_loss: 31228064.0000 - val_mae: 3347.9373\n",
            "Epoch 71/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 17457904.0000 - mae: 2860.7885 - val_loss: 34226020.0000 - val_mae: 3545.3833\n",
            "Epoch 72/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17694764.6875 - mae: 3008.6139 - val_loss: 27093686.0000 - val_mae: 3054.2063\n",
            "Epoch 73/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 27167741.7500 - mae: 3479.6836 - val_loss: 30789038.0000 - val_mae: 3376.3074\n",
            "Epoch 74/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18934695.1250 - mae: 2728.1665 - val_loss: 30836064.0000 - val_mae: 3404.9402\n",
            "Epoch 75/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18361546.2500 - mae: 3108.6033 - val_loss: 31009184.0000 - val_mae: 3413.6011\n",
            "Epoch 76/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11239423.1875 - mae: 2520.3657 - val_loss: 32796012.0000 - val_mae: 3615.4709\n",
            "Epoch 77/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11902781.5938 - mae: 2678.7142 - val_loss: 26429974.0000 - val_mae: 3157.1440\n",
            "Epoch 78/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 10533193.8750 - mae: 2418.7733 - val_loss: 26733234.0000 - val_mae: 3153.7954\n",
            "Epoch 79/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 19323106.8750 - mae: 2937.5440 - val_loss: 30721918.0000 - val_mae: 3524.0125\n",
            "Epoch 80/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15464982.5000 - mae: 2826.4127 - val_loss: 28945372.0000 - val_mae: 3379.8567\n",
            "Epoch 81/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16347410.1250 - mae: 2875.0366 - val_loss: 32154730.0000 - val_mae: 3668.5952\n",
            "Epoch 82/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16578524.5000 - mae: 2940.2445 - val_loss: 30407552.0000 - val_mae: 3515.2209\n",
            "Epoch 83/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 11130631.8438 - mae: 2470.6995 - val_loss: 27669116.0000 - val_mae: 3353.2849\n",
            "Epoch 84/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 12100687.1875 - mae: 2598.5293 - val_loss: 26131338.0000 - val_mae: 3220.8445\n",
            "Epoch 85/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18095923.4375 - mae: 3007.6258 - val_loss: 28224302.0000 - val_mae: 3427.9595\n",
            "Epoch 86/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 14051442.1562 - mae: 2563.1008 - val_loss: 25760588.0000 - val_mae: 3192.6448\n",
            "Epoch 87/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16819167.5625 - mae: 2826.0326 - val_loss: 26128738.0000 - val_mae: 3198.0017\n",
            "Epoch 88/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15072705.3125 - mae: 2732.3450 - val_loss: 25511428.0000 - val_mae: 3188.6716\n",
            "Epoch 89/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15316878.3125 - mae: 2780.7868 - val_loss: 25945632.0000 - val_mae: 3201.4319\n",
            "Epoch 90/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 20242368.1250 - mae: 2890.3006 - val_loss: 26489750.0000 - val_mae: 3227.8188\n",
            "Epoch 91/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 15723405.3750 - mae: 2464.0722 - val_loss: 32703354.0000 - val_mae: 3683.6523\n",
            "Epoch 92/100\n",
            "15/15 [==============================] - 0s 7ms/step - loss: 9583480.9375 - mae: 2429.6603 - val_loss: 32491440.0000 - val_mae: 3650.8972\n",
            "Epoch 93/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 22867761.7500 - mae: 2981.8554 - val_loss: 30754016.0000 - val_mae: 3542.8801\n",
            "Epoch 94/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 10353730.2188 - mae: 2379.1215 - val_loss: 31354554.0000 - val_mae: 3592.7903\n",
            "Epoch 95/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18152780.6875 - mae: 2957.8853 - val_loss: 29397292.0000 - val_mae: 3458.8547\n",
            "Epoch 96/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 17988523.6250 - mae: 2701.2213 - val_loss: 29228378.0000 - val_mae: 3499.7673\n",
            "Epoch 97/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 18194566.0938 - mae: 2814.1393 - val_loss: 23637952.0000 - val_mae: 3041.6379\n",
            "Epoch 98/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 16551052.4688 - mae: 2723.9765 - val_loss: 26267710.0000 - val_mae: 3278.4475\n",
            "Epoch 99/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 13354788.1406 - mae: 2437.6596 - val_loss: 30653268.0000 - val_mae: 3658.2554\n",
            "Epoch 100/100\n",
            "15/15 [==============================] - 0s 6ms/step - loss: 26402710.3750 - mae: 3130.5869 - val_loss: 29690226.0000 - val_mae: 3564.1401\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y6f-oqnXT2T_"
      },
      "source": [
        "## **Finalizing Our Model and Testing on Test Data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8evHBiD6E5aN",
        "outputId": "c51edf3e-a9a2-4bda-bc6d-e358a7b9a272"
      },
      "source": [
        "model = build_model()\n",
        "model.fit(train_data, train_prices,\n",
        "          epochs = 50, batch_size = 8, verbose = 0)\n",
        "\n",
        "test_mse , test_mae = model.evaluate(test_data, test_prices)\n"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2/2 [==============================] - 0s 11ms/step - loss: 9155862.0000 - mae: 2339.4297\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3C72gJmMROnA",
        "outputId": "3dd5e094-3633-4528-9ae3-0bd98805dece"
      },
      "source": [
        "test_mae"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2339.4296875"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VAIGJKvtRQiS"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}