BEST_MODEL_SELECTION.ipynb

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    "colab": {
      "name": "BEST_MODEL_SELECTION",
      "provenance": []
    },
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      "name": "python3",
      "display_name": "Python 3"
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  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "ov_T2JBMdEFV"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q7dTYZ9kdwnx",
        "outputId": "15344100-1ca4-4a59-8009-26fc1ad8f169",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        }
      },
      "source": [
        "train= pd.read_csv('football_CLEAN.csv')\n",
        "train.head()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>club</th>\n",
              "      <th>age</th>\n",
              "      <th>position</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_sel</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>nationality</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alexis Sanchez</td>\n",
              "      <td>Arsenal</td>\n",
              "      <td>28</td>\n",
              "      <td>LW</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>17.10%</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>Chile</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Mesut Ozil</td>\n",
              "      <td>Arsenal</td>\n",
              "      <td>28</td>\n",
              "      <td>AM</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>5.60%</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>Germany</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Petr Cech</td>\n",
              "      <td>Arsenal</td>\n",
              "      <td>35</td>\n",
              "      <td>GK</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>5.90%</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>Czech Republic</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Theo Walcott</td>\n",
              "      <td>Arsenal</td>\n",
              "      <td>28</td>\n",
              "      <td>RW</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>England</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Laurent Koscielny</td>\n",
              "      <td>Arsenal</td>\n",
              "      <td>31</td>\n",
              "      <td>CB</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>France</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                name     club  age  ... club_id  big_club  new_signing\n",
              "0     Alexis Sanchez  Arsenal   28  ...       1         1            0\n",
              "1         Mesut Ozil  Arsenal   28  ...       1         1            0\n",
              "2          Petr Cech  Arsenal   35  ...       1         1            0\n",
              "3       Theo Walcott  Arsenal   28  ...       1         1            0\n",
              "4  Laurent Koscielny  Arsenal   31  ...       1         1            0\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
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          "base_uri": "https://localhost:8080/",
          "height": 241
        }
      },
      "source": [
        "train.drop(['name'],axis=1,inplace=True)\n",
        "train.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>club</th>\n",
              "      <th>age</th>\n",
              "      <th>position</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_sel</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>nationality</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Arsenal</td>\n",
              "      <td>28</td>\n",
              "      <td>LW</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>17.10%</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>Chile</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Arsenal</td>\n",
              "      <td>28</td>\n",
              "      <td>AM</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>5.60%</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>Germany</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Arsenal</td>\n",
              "      <td>35</td>\n",
              "      <td>GK</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>5.90%</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>Czech Republic</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Arsenal</td>\n",
              "      <td>28</td>\n",
              "      <td>RW</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>England</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Arsenal</td>\n",
              "      <td>31</td>\n",
              "      <td>CB</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>France</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      club  age position  position_cat  ...  age_cat  club_id  big_club new_signing\n",
              "0  Arsenal   28       LW             1  ...        4        1         1           0\n",
              "1  Arsenal   28       AM             1  ...        4        1         1           0\n",
              "2  Arsenal   35       GK             4  ...        6        1         1           0\n",
              "3  Arsenal   28       RW             1  ...        4        1         1           0\n",
              "4  Arsenal   31       CB             3  ...        4        1         1           0\n",
              "\n",
              "[5 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
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      "metadata": {
        "id": "dmim8CnhdwtR",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        }
      },
      "source": [
        "train.drop(['club'],axis=1,inplace=True)\n",
        "train.head()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>position</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_sel</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>nationality</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>28</td>\n",
              "      <td>LW</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>17.10%</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>Chile</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>28</td>\n",
              "      <td>AM</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>5.60%</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>Germany</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35</td>\n",
              "      <td>GK</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>5.90%</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>Czech Republic</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>RW</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>England</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>31</td>\n",
              "      <td>CB</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>France</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age position  position_cat  ...  club_id  big_club  new_signing\n",
              "0   28       LW             1  ...        1         1            0\n",
              "1   28       AM             1  ...        1         1            0\n",
              "2   35       GK             4  ...        1         1            0\n",
              "3   28       RW             1  ...        1         1            0\n",
              "4   31       CB             3  ...        1         1            0\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BDqIGSaudwwk",
        "outputId": "32005440-d09e-428b-a30b-a590302b4a35",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train.drop(['position'],axis=1,inplace=True)\n",
        "train.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_sel</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>nationality</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>17.10%</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>Chile</td>\n",
              "      <td>0</td>\n",
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              "      <th>1</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>5.60%</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>Germany</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>5.90%</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>Czech Republic</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>England</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>31</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>France</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  position_cat  market_value  ...  club_id  big_club new_signing\n",
              "0   28             1          65.0  ...        1         1           0\n",
              "1   28             1          50.0  ...        1         1           0\n",
              "2   35             4           7.0  ...        1         1           0\n",
              "3   28             1          20.0  ...        1         1           0\n",
              "4   31             3          22.0  ...        1         1           0\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pNd7uZWidwzQ",
        "outputId": "ae6da611-214b-4cfe-84c7-d1e54817d5ef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train.drop(['nationality'],axis=1,inplace=True)\n",
        "train.head()"
      ],
      "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",
              "    .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>age</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_sel</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>17.10%</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>5.60%</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>5.90%</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>31</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  position_cat  market_value  ...  club_id  big_club new_signing\n",
              "0   28             1          65.0  ...        1         1           0\n",
              "1   28             1          50.0  ...        1         1           0\n",
              "2   35             4           7.0  ...        1         1           0\n",
              "3   28             1          20.0  ...        1         1           0\n",
              "4   31             3          22.0  ...        1         1           0\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rv2oJWfUdw2k",
        "outputId": "39418d22-9a93-412c-853b-523ece10d044",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train['FPL_SEL'] = pd.to_numeric(train['fpl_sel'].str[:-1])\n",
        "train.head()"
      ],
      "execution_count": 10,
      "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>age</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_sel</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "      <th>FPL_SEL</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>17.10%</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>17.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>5.60%</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>5.90%</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>31</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  position_cat  market_value  ...  big_club  new_signing FPL_SEL\n",
              "0   28             1          65.0  ...         1            0    17.1\n",
              "1   28             1          50.0  ...         1            0     5.6\n",
              "2   35             4           7.0  ...         1            0     5.9\n",
              "3   28             1          20.0  ...         1            0     1.5\n",
              "4   31             3          22.0  ...         1            0     0.7\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iohUFZJ1dw5R",
        "outputId": "e3ad36c9-2c15-4b25-a56b-172738052399",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train.drop(['fpl_sel'],axis=1,inplace=True)\n",
        "train.head()"
      ],
      "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>age</th>\n",
              "      <th>position_cat</th>\n",
              "      <th>market_value</th>\n",
              "      <th>page_views</th>\n",
              "      <th>fpl_value</th>\n",
              "      <th>fpl_points</th>\n",
              "      <th>region</th>\n",
              "      <th>new_foreign</th>\n",
              "      <th>age_cat</th>\n",
              "      <th>club_id</th>\n",
              "      <th>big_club</th>\n",
              "      <th>new_signing</th>\n",
              "      <th>FPL_SEL</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>65.0</td>\n",
              "      <td>4329</td>\n",
              "      <td>12.0</td>\n",
              "      <td>264</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>17.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>4395</td>\n",
              "      <td>9.5</td>\n",
              "      <td>167</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>35</td>\n",
              "      <td>4</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1529</td>\n",
              "      <td>5.5</td>\n",
              "      <td>134</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>28</td>\n",
              "      <td>1</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2393</td>\n",
              "      <td>7.5</td>\n",
              "      <td>122</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>31</td>\n",
              "      <td>3</td>\n",
              "      <td>22.0</td>\n",
              "      <td>912</td>\n",
              "      <td>6.0</td>\n",
              "      <td>121</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  position_cat  market_value  ...  big_club  new_signing  FPL_SEL\n",
              "0   28             1          65.0  ...         1            0     17.1\n",
              "1   28             1          50.0  ...         1            0      5.6\n",
              "2   35             4           7.0  ...         1            0      5.9\n",
              "3   28             1          20.0  ...         1            0      1.5\n",
              "4   31             3          22.0  ...         1            0      0.7\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ulx2HQdfdw8B"
      },
      "source": [
        "X= train.drop('market_value',axis=1)\n",
        "Y= train['market_value']"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bZRbfFhQdw-z"
      },
      "source": [
        "from sklearn.model_selection  import train_test_split"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fq5eSEXSdxB1",
        "outputId": "774fa6b6-f880-4950-8ccf-077c2b0738fb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.25, random_state=101)\n",
        "print(X_train.shape)\n",
        "print(X_test.shape)\n",
        "print(Y_train.shape)\n",
        "print(Y_test.shape)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(345, 12)\n",
            "(116, 12)\n",
            "(345,)\n",
            "(116,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E2Dm3GLWdxE3",
        "outputId": "1fc62b5f-4716-4775-fcd4-70ab546b004e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from sklearn.ensemble import GradientBoostingRegressor\n",
        "REGGB = GradientBoostingRegressor(alpha=0.99, learning_rate=0.1, loss='lad', max_depth=6, max_features=1.0, min_samples_leaf=2, min_samples_split=19, n_estimators=100, subsample=0.8)\n",
        "REGGB.fit(X_train, Y_train)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GradientBoostingRegressor(alpha=0.99, ccp_alpha=0.0, criterion='friedman_mse',\n",
              "                          init=None, learning_rate=0.1, loss='lad', max_depth=6,\n",
              "                          max_features=1.0, max_leaf_nodes=None,\n",
              "                          min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                          min_samples_leaf=2, min_samples_split=19,\n",
              "                          min_weight_fraction_leaf=0.0, n_estimators=100,\n",
              "                          n_iter_no_change=None, presort='deprecated',\n",
              "                          random_state=None, subsample=0.8, tol=0.0001,\n",
              "                          validation_fraction=0.1, verbose=0, warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w0h0dtrNdxH1"
      },
      "source": [
        "from sklearn import metrics"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "isANTgxldxKn"
      },
      "source": [
        "pred_GB= REGGB.predict(X_test)"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "leu6u6B8dxNq",
        "outputId": "965fd876-56fd-4946-ada7-186c759240b2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "RMSE = np.sqrt(metrics.mean_squared_error(Y_test, pred_GB))\n",
        "print(RMSE)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4.713341919338422\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WKOZ-f02jd6l",
        "outputId": "bc2f61fa-c7e5-4e09-9f3a-45e668c7e589",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print ('Regression: R^2 score on training set', REGGB.score(X_train,Y_train))\n",
        "print ('Regression: R^2 score on test set', REGGB.score(X_test,Y_test))"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Regression: R^2 score on training set 0.9428107745909174\n",
            "Regression: R^2 score on test set 0.842289869914923\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}