mvp_prediction_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7c2b5add-4943-4967-ade3-f1b20bc48364",
   "metadata": {},
   "outputs": [],
   "source": [
    "import  pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e1ea0798-7f11-48c5-bff2-9da16c9e2ee5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df =  pd.read_csv(\"nba_stats.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e077f66a-9762-43ea-bf1c-e2912b296924",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15614, 53)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1be20565-76b9-406d-a2b9-07f438fd614c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "season            0\n",
       "player            0\n",
       "pos               0\n",
       "age               0\n",
       "experience        0\n",
       "lg_x              0\n",
       "tm                0\n",
       "g                 0\n",
       "gs                0\n",
       "mp                0\n",
       "fg                0\n",
       "fga               0\n",
       "fg_percent        0\n",
       "x3p               0\n",
       "x3pa              0\n",
       "x3p_percent       0\n",
       "x2p               0\n",
       "x2pa              0\n",
       "x2p_percent       0\n",
       "e_fg_percent_x    0\n",
       "ft                0\n",
       "fta               0\n",
       "ft_percent        0\n",
       "orb               0\n",
       "drb               0\n",
       "trb               0\n",
       "ast               0\n",
       "stl               0\n",
       "blk               0\n",
       "tov               0\n",
       "pf                0\n",
       "pts               0\n",
       "pts_won           0\n",
       "pts_max           0\n",
       "share             0\n",
       "team              0\n",
       "w                 0\n",
       "l                 0\n",
       "pw                0\n",
       "pl                0\n",
       "mov               0\n",
       "sos               0\n",
       "srs               0\n",
       "o_rtg             0\n",
       "d_rtg             0\n",
       "n_rtg             0\n",
       "pace              0\n",
       "f_tr              0\n",
       "x3p_ar            0\n",
       "ts_percent        0\n",
       "tov_percent       0\n",
       "orb_percent       0\n",
       "ft_fga            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.isnull(df).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6f808fdc-4b00-4aff-85df-2cbae597ffa5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['player', 'pos', 'lg_x', 'tm', 'team'], dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select_dtypes(include = 'object').columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "de935dd4-6c51-4970-b047-a526ef4000a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['season', 'age', 'experience', 'g', 'gs', 'mp', 'fg', 'fga',\n",
       "       'fg_percent', 'x3p', 'x3pa', 'x3p_percent', 'x2p', 'x2pa',\n",
       "       'x2p_percent', 'e_fg_percent_x', 'ft', 'fta', 'ft_percent', 'orb',\n",
       "       'drb', 'trb', 'ast', 'stl', 'blk', 'tov', 'pf', 'pts', 'pts_won',\n",
       "       'pts_max', 'share', 'w', 'l', 'pw', 'pl', 'mov', 'sos', 'srs', 'o_rtg',\n",
       "       'd_rtg', 'n_rtg', 'pace', 'f_tr', 'x3p_ar', 'ts_percent', 'tov_percent',\n",
       "       'orb_percent', 'ft_fga'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select_dtypes(include = [np.number]).columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0804d125-35ea-4ae1-a560-d7fa791bcdbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000,\n",
       "       2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011,\n",
       "       2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022,\n",
       "       2023])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['season'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d73bbc32-47a6-440c-b8b8-d6b4769321f3",
   "metadata": {},
   "source": [
    "MODELLING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "14d2f420-d69b-44d6-ae7e-939a8900296b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import HistGradientBoostingRegressor, RandomForestRegressor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3ded5481-e09f-4975-97dc-7b42e1072536",
   "metadata": {},
   "outputs": [],
   "source": [
    "train = df[df['season'] <= 2022]\n",
    "test = df[df['season'] == 2023]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6852abc5-d9ce-44eb-a9ad-4dd0fa1231c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#predictors contain categorical features\n",
    "predictors = ['season', 'age', 'experience', 'g', 'gs', 'mp', 'fg', 'fga',\n",
    "       'fg_percent', 'x3p', 'x3pa', 'x3p_percent', 'x2p', 'x2pa',\n",
    "       'x2p_percent', 'e_fg_percent_x', 'ft', 'fta', 'ft_percent', 'orb',\n",
    "       'drb', 'trb', 'ast', 'stl', 'blk', 'tov', 'pf', 'pts',\n",
    "        'w', 'l', 'pw', 'pl', 'mov', 'sos', 'srs', 'o_rtg',\n",
    "       'd_rtg', 'n_rtg', 'pace', 'f_tr', 'x3p_ar', 'ts_percent', 'tov_percent',\n",
    "       'orb_percent', 'ft_fga', 'pos', 'team']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "459a65fc-c210-4d06-8634-a264ada8e52c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#defining the histogram estimators\n",
    "hst = HistGradientBoostingRegressor(\n",
    "    categorical_features =[\"pos\", \"team\"], random_state = 42\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8f95ae6a-f082-493d-bc49-993b2e6619e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "HistGradientBoostingRegressor(categorical_features=['pos', 'team'], max_depth=5,\n",
       "                              max_iter=150, random_state=42)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hst.fit(train[predictors], train['share'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a76b3397-b11b-47cc-b619-4843d96ceebc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "HistGradientBoostingRegressor(categorical_features=['pos', 'team'], max_depth=5,\n",
       "                              max_iter=150, random_state=42)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hst.set_params(loss='squared_error', max_depth=5, max_iter =150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f2a16b79-89af-4a28-b60a-5d95c932bf2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "preds = hst.predict(test[predictors])\n",
    "preds = pd.DataFrame(preds, columns = [\"predicted\"], index = test.index)\n",
    "\n",
    "result = pd.concat([test[['player', 'share']], preds], axis =1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e74eecca-e712-495c-ad09-56ca0aae8746",
   "metadata": {},
   "outputs": [
    {
     "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>player</th>\n",
       "      <th>share</th>\n",
       "      <th>predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15100</th>\n",
       "      <td>Jayson Tatum</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.663952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15362</th>\n",
       "      <td>Giannis Antetokounmpo</td>\n",
       "      <td>0.606</td>\n",
       "      <td>0.603496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15466</th>\n",
       "      <td>Joel Embiid</td>\n",
       "      <td>0.915</td>\n",
       "      <td>0.441183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15439</th>\n",
       "      <td>Shai Gilgeous-Alexander</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.232159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15214</th>\n",
       "      <td>Nikola Jokić</td>\n",
       "      <td>0.674</td>\n",
       "      <td>0.183423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15195</th>\n",
       "      <td>Kyrie Irving</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.020808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15521</th>\n",
       "      <td>Harrison Barnes</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.022576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15122</th>\n",
       "      <td>Mikal Bridges</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.024837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15138</th>\n",
       "      <td>DeMar DeRozan</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.025318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15130</th>\n",
       "      <td>Spencer Dinwiddie</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.028075</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>538 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        player  share  predicted\n",
       "15100             Jayson Tatum  0.280   0.663952\n",
       "15362    Giannis Antetokounmpo  0.606   0.603496\n",
       "15466              Joel Embiid  0.915   0.441183\n",
       "15439  Shai Gilgeous-Alexander  0.046   0.232159\n",
       "15214             Nikola Jokić  0.674   0.183423\n",
       "...                        ...    ...        ...\n",
       "15195             Kyrie Irving  0.000  -0.020808\n",
       "15521          Harrison Barnes  0.000  -0.022576\n",
       "15122            Mikal Bridges  0.000  -0.024837\n",
       "15138            DeMar DeRozan  0.000  -0.025318\n",
       "15130        Spencer Dinwiddie  0.000  -0.028075\n",
       "\n",
       "[538 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.sort_values('predicted', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6b7cfcb7-9b6b-42b5-b5b4-71157958f299",
   "metadata": {},
   "outputs": [],
   "source": [
    "result = result.sort_values(\"share\", ascending =False)\n",
    "result['Rk'] = list(range(1, result.shape[0]+1))\n",
    "\n",
    "result = result.sort_values(\"predicted\", ascending =False).head(10)\n",
    "result['preds_Rk'] = list(range(1, result.shape[0]+1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "26dd5c7c-d1a4-4a16-ada0-d9c10c9e2aac",
   "metadata": {},
   "outputs": [
    {
     "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>player</th>\n",
       "      <th>share</th>\n",
       "      <th>predicted</th>\n",
       "      <th>Rk</th>\n",
       "      <th>preds_Rk</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15100</th>\n",
       "      <td>Jayson Tatum</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.663952</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15362</th>\n",
       "      <td>Giannis Antetokounmpo</td>\n",
       "      <td>0.606</td>\n",
       "      <td>0.603496</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15466</th>\n",
       "      <td>Joel Embiid</td>\n",
       "      <td>0.915</td>\n",
       "      <td>0.441183</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15439</th>\n",
       "      <td>Shai Gilgeous-Alexander</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.232159</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15214</th>\n",
       "      <td>Nikola Jokić</td>\n",
       "      <td>0.674</td>\n",
       "      <td>0.183423</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15171</th>\n",
       "      <td>Donovan Mitchell</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.169927</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15099</th>\n",
       "      <td>Jaylen Brown</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.117386</td>\n",
       "      <td>350</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15090</th>\n",
       "      <td>Trae Young</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.104444</td>\n",
       "      <td>359</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15418</th>\n",
       "      <td>Julius Randle</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.065199</td>\n",
       "      <td>111</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15196</th>\n",
       "      <td>Luka Dončić</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.064541</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        player  share  predicted   Rk  preds_Rk\n",
       "15100             Jayson Tatum  0.280   0.663952    4         1\n",
       "15362    Giannis Antetokounmpo  0.606   0.603496    3         2\n",
       "15466              Joel Embiid  0.915   0.441183    1         3\n",
       "15439  Shai Gilgeous-Alexander  0.046   0.232159    5         4\n",
       "15214             Nikola Jokić  0.674   0.183423    2         5\n",
       "15171         Donovan Mitchell  0.030   0.169927    6         6\n",
       "15099             Jaylen Brown  0.000   0.117386  350         7\n",
       "15090               Trae Young  0.000   0.104444  359         8\n",
       "15418            Julius Randle  0.000   0.065199  111         9\n",
       "15196              Luka Dončić  0.010   0.064541    8        10"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e37e76b-dd72-4e93-b5e1-6e8c57bc7ece",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "fa4d9e5e-8420-4d50-ad0e-f5553ac3ee4a",
   "metadata": {},
   "source": [
    "METRICS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fee8d714-24b0-4e0e-b357-6230717502f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_absolute_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "98bae06e-369e-4c14-8c88-10475719b4e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.2018506254418772)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mea = mean_absolute_error(result['share'], result['predicted'])\n",
    "mea\n",
    "#At top 10, the model is ~20% wrong"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "70e93630-58c0-4745-91a1-ae5400b598be",
   "metadata": {},
   "outputs": [],
   "source": [
    "#custom averaged precision\n",
    "def find_ap(result):\n",
    "    actual = result.sort_values('share', ascending = False).head(6)\n",
    "    predicted = result.sort_values('predicted', ascending = False)\n",
    "    ps = []\n",
    "    found = 0\n",
    "    seen = 1\n",
    "    for index, row in predicted.iterrows():\n",
    "        if row['player'] in actual['player'].values:\n",
    "            found += 1\n",
    "            ps.append(found/seen)\n",
    "\n",
    "        seen += 1\n",
    "    return sum(ps)/len(ps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7a7654dc-37b9-4ed5-8097-a1678b9a2a34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "find_ap(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f745e92-d670-467f-ad3a-0109f9377c70",
   "metadata": {},
   "source": [
    "OPTIMIZING PARAMETERS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "93af69d5-8871-4710-b59c-6faf7a13f005",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'categorical_features': ['pos', 'team'],\n",
       " 'early_stopping': 'auto',\n",
       " 'interaction_cst': None,\n",
       " 'l2_regularization': 0.0,\n",
       " 'learning_rate': 0.1,\n",
       " 'loss': 'squared_error',\n",
       " 'max_bins': 255,\n",
       " 'max_depth': 5,\n",
       " 'max_features': 1.0,\n",
       " 'max_iter': 150,\n",
       " 'max_leaf_nodes': 31,\n",
       " 'min_samples_leaf': 20,\n",
       " 'monotonic_cst': None,\n",
       " 'n_iter_no_change': 10,\n",
       " 'quantile': None,\n",
       " 'random_state': 42,\n",
       " 'scoring': 'loss',\n",
       " 'tol': 1e-07,\n",
       " 'validation_fraction': 0.1,\n",
       " 'verbose': 0,\n",
       " 'warm_start': False}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hst.get_params()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "371f9267-edf0-495d-8884-3b8977f6e156",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Aim to obtain ~10% mean absolute error\n",
    "from sklearn.model_selection import GridSearchCV, RepeatedKFold\n",
    "param_grid = {\n",
    "    'max_depth' : [5,10, 15,25],\n",
    "    'max_iter' : [50,75, 100, 150],\n",
    "    'loss' : ['squared_error', 'absolute_error']  \n",
    "}\n",
    "\n",
    "cv = RepeatedKFold(n_splits =2, n_repeats =5, random_state=42)\n",
    "\n",
    "grid = GridSearchCV(hst, param_grid = param_grid, cv=cv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e08d222d-2582-43c1-9721-5f31b33a1fb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-4 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-4 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-4 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-4 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "             estimator=HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;,\n",
       "                                                                           &#x27;team&#x27;],\n",
       "                                                     max_depth=5, max_iter=150,\n",
       "                                                     random_state=42),\n",
       "             param_grid={&#x27;loss&#x27;: [&#x27;squared_error&#x27;, &#x27;absolute_error&#x27;],\n",
       "                         &#x27;max_depth&#x27;: [5, 10, 15, 25],\n",
       "                         &#x27;max_iter&#x27;: [50, 75, 100, 150]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;GridSearchCV<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>GridSearchCV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "             estimator=HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;,\n",
       "                                                                           &#x27;team&#x27;],\n",
       "                                                     max_depth=5, max_iter=150,\n",
       "                                                     random_state=42),\n",
       "             param_grid={&#x27;loss&#x27;: [&#x27;squared_error&#x27;, &#x27;absolute_error&#x27;],\n",
       "                         &#x27;max_depth&#x27;: [5, 10, 15, 25],\n",
       "                         &#x27;max_iter&#x27;: [50, 75, 100, 150]})</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">estimator: HistGradientBoostingRegressor</label><div class=\"sk-toggleable__content \"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content \"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "             estimator=HistGradientBoostingRegressor(categorical_features=['pos',\n",
       "                                                                           'team'],\n",
       "                                                     max_depth=5, max_iter=150,\n",
       "                                                     random_state=42),\n",
       "             param_grid={'loss': ['squared_error', 'absolute_error'],\n",
       "                         'max_depth': [5, 10, 15, 25],\n",
       "                         'max_iter': [50, 75, 100, 150]})"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f514d358-8bb3-46cd-919f-5697f7827163",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-4 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-4 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-4 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-4 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-4 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-4 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-4 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "             estimator=HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;,\n",
       "                                                                           &#x27;team&#x27;],\n",
       "                                                     random_state=42),\n",
       "             param_grid={&#x27;loss&#x27;: [&#x27;squared_error&#x27;, &#x27;absolute_error&#x27;],\n",
       "                         &#x27;max_depth&#x27;: [5, 10, 15, 25],\n",
       "                         &#x27;max_iter&#x27;: [50, 75, 100, 150]})</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" ><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;GridSearchCV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.model_selection.GridSearchCV.html\">?<span>Documentation for GridSearchCV</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>GridSearchCV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "             estimator=HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;,\n",
       "                                                                           &#x27;team&#x27;],\n",
       "                                                     random_state=42),\n",
       "             param_grid={&#x27;loss&#x27;: [&#x27;squared_error&#x27;, &#x27;absolute_error&#x27;],\n",
       "                         &#x27;max_depth&#x27;: [5, 10, 15, 25],\n",
       "                         &#x27;max_iter&#x27;: [50, 75, 100, 150]})</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-19\" type=\"checkbox\" ><label for=\"sk-estimator-id-19\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: HistGradientBoostingRegressor</label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;],\n",
       "                              random_state=42)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-20\" type=\"checkbox\" ><label for=\"sk-estimator-id-20\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;],\n",
       "                              random_state=42)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "GridSearchCV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "             estimator=HistGradientBoostingRegressor(categorical_features=['pos',\n",
       "                                                                           'team'],\n",
       "                                                     random_state=42),\n",
       "             param_grid={'loss': ['squared_error', 'absolute_error'],\n",
       "                         'max_depth': [5, 10, 15, 25],\n",
       "                         'max_iter': [50, 75, 100, 150]})"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.fit(train[predictors], train['share'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0c214fd8-16ec-471f-8c42-08a6175564ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'loss': 'squared_error', 'max_depth': 5, 'max_iter': 150}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2ed7c0bc-a3d2-439c-bc2a-1e0a5503559e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-5 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-5 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-5 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-5 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-5 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-5 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-5 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-21\" type=\"checkbox\" checked><label for=\"sk-estimator-id-21\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(categorical_features=[&#x27;pos&#x27;, &#x27;team&#x27;], max_depth=5,\n",
       "                              max_iter=150, random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "HistGradientBoostingRegressor(categorical_features=['pos', 'team'], max_depth=5,\n",
       "                              max_iter=150, random_state=42)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7e98090-78e0-4df5-856a-ca9f8408a1d5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "73bb786e-214a-41bc-9e97-4b7131416798",
   "metadata": {},
   "source": [
    "BACKTESTING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "76e96c2f-cdf6-449a-911f-b54c67acbdf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "years = list(range(1991, 2024))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "06a0d1b7-c2bc-4d68-83f6-f0d4f9530a81",
   "metadata": {},
   "outputs": [],
   "source": [
    "def backtest(df, model, year, predictions):\n",
    "    aps = []\n",
    "    all_predictions  = []\n",
    "    for year in years[5:]:\n",
    "        train = df[df['season'] < year]\n",
    "        test = df[df['season'] == year]\n",
    "        model.fit(train[predictors], train['share'])\n",
    "        prediction = model.predict(test[predictors])\n",
    "        prediction  = pd.DataFrame(prediction, columns = ['predicted'], index = test.index)\n",
    "        result = pd.concat([test[['player', 'season', 'share']], prediction], axis =1)\n",
    "\n",
    "        result = result.sort_values('share', ascending= False)\n",
    "        result['Rk'] = list(range(1, result.shape[0] +1))\n",
    "        result = result.sort_values('predicted', ascending= False).head(10)\n",
    "        result['preds_Rk'] = list(range(1, result.shape[0] +1))\n",
    "        result['diff'] = result['Rk'] - result['preds_Rk']\n",
    "    \n",
    "        all_predictions.append(result)\n",
    "        aps.append(find_ap(result))\n",
    "\n",
    "    return sum(aps)/len(aps), aps, pd.concat(all_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "260759ee-84e2-4ea6-bb8e-b43ff64d3f56",
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_aps, aps, prediction = backtest(df, hst, years[5:], predictors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9426a69c-d369-446d-9e1a-fef48d5943c9",
   "metadata": {},
   "outputs": [
    {
     "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>player</th>\n",
       "      <th>season</th>\n",
       "      <th>share</th>\n",
       "      <th>predicted</th>\n",
       "      <th>Rk</th>\n",
       "      <th>preds_Rk</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2405</th>\n",
       "      <td>Michael Jordan</td>\n",
       "      <td>1996</td>\n",
       "      <td>0.986</td>\n",
       "      <td>0.644927</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2742</th>\n",
       "      <td>Karl Malone</td>\n",
       "      <td>1996</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.529927</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2694</th>\n",
       "      <td>David Robinson</td>\n",
       "      <td>1996</td>\n",
       "      <td>0.508</td>\n",
       "      <td>0.451935</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2613</th>\n",
       "      <td>Anfernee Hardaway</td>\n",
       "      <td>1996</td>\n",
       "      <td>0.319</td>\n",
       "      <td>0.317664</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2711</th>\n",
       "      <td>Shawn Kemp</td>\n",
       "      <td>1996</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.190957</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>3</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15171</th>\n",
       "      <td>Donovan Mitchell</td>\n",
       "      <td>2023</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.169927</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15099</th>\n",
       "      <td>Jaylen Brown</td>\n",
       "      <td>2023</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.117386</td>\n",
       "      <td>350</td>\n",
       "      <td>7</td>\n",
       "      <td>343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15090</th>\n",
       "      <td>Trae Young</td>\n",
       "      <td>2023</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.104444</td>\n",
       "      <td>359</td>\n",
       "      <td>8</td>\n",
       "      <td>351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15418</th>\n",
       "      <td>Julius Randle</td>\n",
       "      <td>2023</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.065199</td>\n",
       "      <td>111</td>\n",
       "      <td>9</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15196</th>\n",
       "      <td>Luka Dončić</td>\n",
       "      <td>2023</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.064541</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>280 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  player  season  share  predicted   Rk  preds_Rk  diff\n",
       "2405      Michael Jordan    1996  0.986   0.644927    1         1     0\n",
       "2742         Karl Malone    1996  0.075   0.529927    7         2     5\n",
       "2694      David Robinson    1996  0.508   0.451935    2         3    -1\n",
       "2613   Anfernee Hardaway    1996  0.319   0.317664    3         4    -1\n",
       "2711          Shawn Kemp    1996  0.065   0.190957    8         5     3\n",
       "...                  ...     ...    ...        ...  ...       ...   ...\n",
       "15171   Donovan Mitchell    2023  0.030   0.169927    6         6     0\n",
       "15099       Jaylen Brown    2023  0.000   0.117386  350         7   343\n",
       "15090         Trae Young    2023  0.000   0.104444  359         8   351\n",
       "15418      Julius Randle    2023  0.000   0.065199  111         9   102\n",
       "15196        Luka Dončić    2023  0.010   0.064541    8        10    -2\n",
       "\n",
       "[280 rows x 7 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "adb2eba1-8971-43b7-9b7c-a730b66acc6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9024022108843538"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_aps\n",
    "#over the years baacktesting, the model maintains a 0.90% predictions for top 10 MVP "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5aa108b3-7f26-449b-b8b9-3bb5d4e19085",
   "metadata": {},
   "outputs": [
    {
     "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>player</th>\n",
       "      <th>season</th>\n",
       "      <th>share</th>\n",
       "      <th>predicted</th>\n",
       "      <th>Rk</th>\n",
       "      <th>preds_Rk</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14070</th>\n",
       "      <td>Nikola Jokić</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.961</td>\n",
       "      <td>0.430861</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14358</th>\n",
       "      <td>Devin Booker</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.198143</td>\n",
       "      <td>219</td>\n",
       "      <td>2</td>\n",
       "      <td>217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14050</th>\n",
       "      <td>Luka Dončić</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0.127693</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14227</th>\n",
       "      <td>Giannis Antetokounmpo</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.345</td>\n",
       "      <td>0.120141</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14469</th>\n",
       "      <td>Russell Westbrook</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.103383</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14450</th>\n",
       "      <td>Rudy Gobert</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.093696</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14340</th>\n",
       "      <td>Joel Embiid</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.580</td>\n",
       "      <td>0.047653</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14355</th>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.138</td>\n",
       "      <td>0.043072</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14372</th>\n",
       "      <td>Damian Lillard</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.042010</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14273</th>\n",
       "      <td>Zion Williamson</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.034380</td>\n",
       "      <td>73</td>\n",
       "      <td>10</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      player  season  share  predicted   Rk  preds_Rk  diff\n",
       "14070           Nikola Jokić    2021  0.961   0.430861    1         1     0\n",
       "14358           Devin Booker    2021  0.000   0.198143  219         2   217\n",
       "14050            Luka Dončić    2021  0.042   0.127693    6         3     3\n",
       "14227  Giannis Antetokounmpo    2021  0.345   0.120141    4         4     0\n",
       "14469      Russell Westbrook    2021  0.005   0.103383   11         5     6\n",
       "14450            Rudy Gobert    2021  0.008   0.093696   10         6     4\n",
       "14340            Joel Embiid    2021  0.580   0.047653    2         7    -5\n",
       "14355             Chris Paul    2021  0.138   0.043072    5         8    -3\n",
       "14372         Damian Lillard    2021  0.038   0.042010    7         9    -2\n",
       "14273        Zion Williamson    2021  0.000   0.034380   73        10    63"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Obtain players for MVP predicted each year\n",
    "\n",
    "mvp = prediction.groupby('season', group_keys = False)\n",
    "\n",
    "mvp.get_group(2021)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2252c50-46af-472d-976e-ddcb0e1e7898",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4a9b6c8b-50ce-439c-8666-1342e855328e",
   "metadata": {},
   "source": [
    "EVALUATING THE MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "91800c92-6868-42b1-9da1-e62746080ad3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.inspection import permutation_importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7bb01d91-609f-4292-9d6a-978289331e33",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_importance = permutation_importance(\n",
    "    hst, train[predictors], train['share'], random_state = 42, n_repeats = 10, n_jobs = 2\n",
    ")\n",
    "\n",
    "test_importance = permutation_importance(\n",
    "    hst, test[predictors], test['share'], random_state = 42, n_repeats = 10, n_jobs = 2\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f2cbcff4-9a9a-4e27-9334-24895945a426",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "       [ 7.55831848e-02],\n",
       "       [ 1.18679226e-02],\n",
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       "       [ 9.89644685e-03],\n",
       "       [ 9.14989310e-03],\n",
       "       [ 8.25049298e-03],\n",
       "       [ 4.07152566e-01],\n",
       "       [ 4.34273163e-01],\n",
       "       [ 3.78358624e-01],\n",
       "       [ 4.01069026e-01],\n",
       "       [ 3.81438896e-01],\n",
       "       [ 3.96799533e-01],\n",
       "       [ 3.58425874e-01],\n",
       "       [ 4.04611647e-01],\n",
       "       [ 3.75046195e-01],\n",
       "       [ 3.89550590e-01],\n",
       "       [ 2.30557217e-02],\n",
       "       [ 2.61142432e-02],\n",
       "       [ 2.38679274e-02],\n",
       "       [ 2.44130430e-02],\n",
       "       [ 2.43639101e-02],\n",
       "       [ 2.20715241e-02],\n",
       "       [ 2.61336513e-02],\n",
       "       [ 2.01722249e-02],\n",
       "       [ 3.16268451e-02],\n",
       "       [ 2.51767533e-02],\n",
       "       [ 1.67023371e-01],\n",
       "       [ 1.56535423e-01],\n",
       "       [ 1.60509722e-01],\n",
       "       [ 1.45372800e-01],\n",
       "       [ 1.47576382e-01],\n",
       "       [ 1.43849303e-01],\n",
       "       [ 1.71895906e-01],\n",
       "       [ 1.36871785e-01],\n",
       "       [ 1.70699250e-01],\n",
       "       [ 1.61382352e-01],\n",
       "       [ 2.33160788e-03],\n",
       "       [ 2.31178090e-03],\n",
       "       [ 1.88305054e-03],\n",
       "       [ 2.03664828e-03],\n",
       "       [ 2.12532327e-03],\n",
       "       [ 1.59832858e-03],\n",
       "       [ 1.62253825e-03],\n",
       "       [ 2.01036146e-03],\n",
       "       [ 2.69050064e-03],\n",
       "       [ 2.28097376e-03],\n",
       "       [ 1.16480071e-02],\n",
       "       [ 1.08512830e-02],\n",
       "       [ 1.13152118e-02],\n",
       "       [ 1.08156616e-02],\n",
       "       [ 1.01039249e-02],\n",
       "       [ 9.18789397e-03],\n",
       "       [ 1.37414848e-02],\n",
       "       [ 1.07836570e-02],\n",
       "       [ 1.27630039e-02],\n",
       "       [ 1.04332688e-02],\n",
       "       [ 8.96829747e-03],\n",
       "       [ 7.91381326e-03],\n",
       "       [ 8.08040198e-03],\n",
       "       [ 7.84345437e-03],\n",
       "       [ 8.38294976e-03],\n",
       "       [ 8.54784134e-03],\n",
       "       [ 8.17334219e-03],\n",
       "       [ 7.48206871e-03],\n",
       "       [ 8.26867088e-03],\n",
       "       [ 8.10261755e-03],\n",
       "       [ 1.65010646e-03],\n",
       "       [ 1.72392643e-03],\n",
       "       [ 2.00496802e-03],\n",
       "       [ 1.92991408e-03],\n",
       "       [ 2.01369008e-03],\n",
       "       [ 1.81657801e-03],\n",
       "       [ 1.88213205e-03],\n",
       "       [ 1.96143047e-03],\n",
       "       [ 1.45321921e-03],\n",
       "       [ 1.89341719e-03],\n",
       "       [ 2.49439876e-02],\n",
       "       [ 2.45403264e-02],\n",
       "       [ 2.50973804e-02],\n",
       "       [ 2.65200235e-02],\n",
       "       [ 2.43891060e-02],\n",
       "       [ 1.70972447e-02],\n",
       "       [ 2.91556345e-02],\n",
       "       [ 2.17932841e-02],\n",
       "       [ 3.13888976e-02],\n",
       "       [ 3.08251269e-02],\n",
       "       [ 3.79291809e-03],\n",
       "       [ 3.36952737e-03],\n",
       "       [ 3.40775769e-03],\n",
       "       [ 4.16045192e-03],\n",
       "       [ 3.98164932e-03],\n",
       "       [ 3.86638457e-03],\n",
       "       [ 3.26161737e-03],\n",
       "       [ 3.98046757e-03],\n",
       "       [ 3.15593037e-03],\n",
       "       [ 3.92291772e-03],\n",
       "       [ 6.78403992e-03],\n",
       "       [ 7.00956269e-03],\n",
       "       [ 5.64754820e-03],\n",
       "       [ 6.84187212e-03],\n",
       "       [ 5.60718779e-03],\n",
       "       [ 6.06689790e-03],\n",
       "       [ 7.59061283e-03],\n",
       "       [ 7.03295331e-03],\n",
       "       [ 5.72632483e-03],\n",
       "       [ 6.94176602e-03],\n",
       "       [ 3.63161787e-03],\n",
       "       [ 3.63807102e-03],\n",
       "       [ 3.72022813e-03],\n",
       "       [ 3.78386129e-03],\n",
       "       [ 3.59233286e-03],\n",
       "       [ 4.09741992e-03],\n",
       "       [ 3.93896817e-03],\n",
       "       [ 2.90170554e-03],\n",
       "       [ 3.70118597e-03],\n",
       "       [ 3.82253393e-03],\n",
       "       [ 1.93043589e-03],\n",
       "       [ 2.29068577e-03],\n",
       "       [ 2.04172283e-03],\n",
       "       [ 1.79494328e-03],\n",
       "       [ 2.05789360e-03],\n",
       "       [ 2.56359233e-03],\n",
       "       [ 1.76067946e-03],\n",
       "       [ 2.52508109e-03],\n",
       "       [ 2.28243727e-03],\n",
       "       [ 2.36526345e-03],\n",
       "       [ 7.44946662e-03],\n",
       "       [ 9.04644035e-03],\n",
       "       [ 8.38539824e-03],\n",
       "       [ 8.47963645e-03],\n",
       "       [ 7.02131300e-03],\n",
       "       [ 7.69711922e-03],\n",
       "       [ 9.53377289e-03],\n",
       "       [ 8.97952992e-03],\n",
       "       [ 9.42451651e-03],\n",
       "       [ 6.63462482e-03],\n",
       "       [ 4.22283730e-03],\n",
       "       [ 5.67761595e-03],\n",
       "       [ 4.63748705e-03],\n",
       "       [ 4.05350993e-03],\n",
       "       [ 4.09240319e-03],\n",
       "       [ 5.05048954e-03],\n",
       "       [ 5.31394429e-03],\n",
       "       [ 4.65307612e-03],\n",
       "       [ 3.69988977e-03],\n",
       "       [ 4.99086336e-03],\n",
       "       [ 3.36557476e-03],\n",
       "       [ 3.20388038e-03],\n",
       "       [ 3.46027228e-03],\n",
       "       [ 3.04962495e-03],\n",
       "       [ 3.68906302e-03],\n",
       "       [ 3.22278095e-03],\n",
       "       [ 3.69672965e-03],\n",
       "       [ 3.26405864e-03],\n",
       "       [ 2.84830948e-03],\n",
       "       [ 3.76148930e-03],\n",
       "       [ 2.53502887e-03],\n",
       "       [ 3.77174906e-03],\n",
       "       [ 2.48694773e-03],\n",
       "       [ 3.83272850e-03],\n",
       "       [ 2.86575526e-03],\n",
       "       [ 2.38048212e-03],\n",
       "       [ 3.24856459e-03],\n",
       "       [ 3.60020677e-03],\n",
       "       [ 4.25694618e-03],\n",
       "       [ 2.88990459e-03],\n",
       "       [ 4.68654827e-03],\n",
       "       [ 3.58831558e-03],\n",
       "       [ 3.18199263e-03],\n",
       "       [ 3.74138253e-03],\n",
       "       [ 3.76764771e-03],\n",
       "       [ 4.84680806e-03],\n",
       "       [ 3.11533408e-03],\n",
       "       [ 3.21022902e-03],\n",
       "       [ 3.40844208e-03],\n",
       "       [ 3.14571108e-03],\n",
       "       [ 4.87401954e-03],\n",
       "       [ 4.89698433e-03],\n",
       "       [ 4.63518565e-03],\n",
       "       [ 6.07645372e-03],\n",
       "       [ 4.51102814e-03],\n",
       "       [ 5.80028153e-03],\n",
       "       [ 3.79586462e-03],\n",
       "       [ 4.79012835e-03],\n",
       "       [ 5.33135965e-03],\n",
       "       [ 5.74166273e-03],\n",
       "       [ 7.14015322e-04],\n",
       "       [ 1.21937723e-03],\n",
       "       [ 7.25446808e-04],\n",
       "       [ 9.25998112e-04],\n",
       "       [ 8.42107182e-04],\n",
       "       [ 9.91841834e-04],\n",
       "       [ 8.70672899e-04],\n",
       "       [ 1.05384098e-03],\n",
       "       [ 7.25174070e-04],\n",
       "       [ 8.47172951e-04],\n",
       "       [ 8.98692242e-03],\n",
       "       [ 1.14809939e-02],\n",
       "       [ 9.00673723e-03],\n",
       "       [ 8.24064056e-03],\n",
       "       [ 9.03987134e-03],\n",
       "       [ 9.69292943e-03],\n",
       "       [ 8.24079703e-03],\n",
       "       [ 7.82804329e-03],\n",
       "       [ 7.83825017e-03],\n",
       "       [ 1.00975841e-02]])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_importance.importances.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ac4e25b3-5f75-410a-abe2-ec81076c3bec",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "tst = test_importance['importances_mean'].reshape(-1,1)\n",
    "tst = pd.DataFrame(tst, columns=['test'])\n",
    "\n",
    "prd = test[predictors].columns\n",
    "prd = pd.DataFrame(prd, columns =['prd'])\n",
    "\n",
    "trn = train_importance['importances_mean'].reshape(-1,1)\n",
    "trn = pd.DataFrame(trn, columns=['train'])\n",
    "\n",
    "prd_1 = train[predictors].columns\n",
    "prd_1 = pd.DataFrame(prd_1, columns =['prd'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6c9644c2-52a7-4dce-ae9a-9244b2a731b1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "train_imptnce= prd_1.merge(trn, how='outer', on=prd_1.index)\n",
    "train_imptnce = train_imptnce.drop('key_0', axis=1)\n",
    "train_imptnce = train_imptnce.sort_values('train', ascending= False)\n",
    "\n",
    "test_imptnce= prd.merge(tst, how='outer', on=prd.index)\n",
    "test_imptnce = test_imptnce.drop('key_0', axis = 1)\n",
    "test_imptnce = test_imptnce.sort_values('test', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f923a6b2-2322-4396-957c-db3753ff0777",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>prd</th>\n",
       "      <th>train</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>pts</td>\n",
       "      <td>0.392673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>l</td>\n",
       "      <td>0.156172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fg</td>\n",
       "      <td>0.110732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>fta</td>\n",
       "      <td>0.076525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ast</td>\n",
       "      <td>0.070368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>srs</td>\n",
       "      <td>0.025575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>w</td>\n",
       "      <td>0.024700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mp</td>\n",
       "      <td>0.024253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>drb</td>\n",
       "      <td>0.016929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>trb</td>\n",
       "      <td>0.015085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ft</td>\n",
       "      <td>0.014739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>x2pa</td>\n",
       "      <td>0.014639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>blk</td>\n",
       "      <td>0.012716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>stl</td>\n",
       "      <td>0.011778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>pl</td>\n",
       "      <td>0.011164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>x2p</td>\n",
       "      <td>0.011129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>tov</td>\n",
       "      <td>0.010926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>pf</td>\n",
       "      <td>0.010296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>team</td>\n",
       "      <td>0.009045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>g</td>\n",
       "      <td>0.008663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>fg_percent</td>\n",
       "      <td>0.008551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>f_tr</td>\n",
       "      <td>0.008265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>mov</td>\n",
       "      <td>0.008176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>d_rtg</td>\n",
       "      <td>0.006525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ft_percent</td>\n",
       "      <td>0.005434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fga</td>\n",
       "      <td>0.005154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ft_fga</td>\n",
       "      <td>0.005045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>x3p_ar</td>\n",
       "      <td>0.004639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gs</td>\n",
       "      <td>0.004300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>o_rtg</td>\n",
       "      <td>0.003690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>n_rtg</td>\n",
       "      <td>0.003683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>orb_percent</td>\n",
       "      <td>0.003669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ts_percent</td>\n",
       "      <td>0.003356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>tov_percent</td>\n",
       "      <td>0.003187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>x3p</td>\n",
       "      <td>0.002943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>e_fg_percent_x</td>\n",
       "      <td>0.002871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>orb</td>\n",
       "      <td>0.002775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>x2p_percent</td>\n",
       "      <td>0.002623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>pace</td>\n",
       "      <td>0.002161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>pw</td>\n",
       "      <td>0.002089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>x3pa</td>\n",
       "      <td>0.001898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>sos</td>\n",
       "      <td>0.001833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>season</td>\n",
       "      <td>0.001021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>pos</td>\n",
       "      <td>0.000892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>age</td>\n",
       "      <td>0.000131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>x3p_percent</td>\n",
       "      <td>0.000080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>experience</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               prd     train\n",
       "27             pts  0.392673\n",
       "29               l  0.156172\n",
       "6               fg  0.110732\n",
       "17             fta  0.076525\n",
       "22             ast  0.070368\n",
       "34             srs  0.025575\n",
       "28               w  0.024700\n",
       "5               mp  0.024253\n",
       "20             drb  0.016929\n",
       "21             trb  0.015085\n",
       "16              ft  0.014739\n",
       "13            x2pa  0.014639\n",
       "24             blk  0.012716\n",
       "23             stl  0.011778\n",
       "31              pl  0.011164\n",
       "12             x2p  0.011129\n",
       "25             tov  0.010926\n",
       "26              pf  0.010296\n",
       "46            team  0.009045\n",
       "3                g  0.008663\n",
       "8       fg_percent  0.008551\n",
       "39            f_tr  0.008265\n",
       "32             mov  0.008176\n",
       "36           d_rtg  0.006525\n",
       "18      ft_percent  0.005434\n",
       "7              fga  0.005154\n",
       "44          ft_fga  0.005045\n",
       "40          x3p_ar  0.004639\n",
       "4               gs  0.004300\n",
       "35           o_rtg  0.003690\n",
       "37           n_rtg  0.003683\n",
       "43     orb_percent  0.003669\n",
       "41      ts_percent  0.003356\n",
       "42     tov_percent  0.003187\n",
       "9              x3p  0.002943\n",
       "15  e_fg_percent_x  0.002871\n",
       "19             orb  0.002775\n",
       "14     x2p_percent  0.002623\n",
       "38            pace  0.002161\n",
       "30              pw  0.002089\n",
       "10            x3pa  0.001898\n",
       "33             sos  0.001833\n",
       "0           season  0.001021\n",
       "45             pos  0.000892\n",
       "1              age  0.000131\n",
       "11     x3p_percent  0.000080\n",
       "2       experience  0.000000"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_imptnce\n",
    "#the model weighs some \"important\" features very low during training\n",
    "#features such as : experience, age, position\n",
    "#Loss(l) has a significant weight during training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "59d89aaa-4ee0-42dd-92c5-3c7a8bce5c5c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\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>prd</th>\n",
       "      <th>test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>pts</td>\n",
       "      <td>2.335398e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>fta</td>\n",
       "      <td>5.981949e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>fg_percent</td>\n",
       "      <td>5.340742e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>l</td>\n",
       "      <td>4.948543e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>trb</td>\n",
       "      <td>4.088631e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>team</td>\n",
       "      <td>3.834525e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fga</td>\n",
       "      <td>3.322384e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mp</td>\n",
       "      <td>2.356932e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>drb</td>\n",
       "      <td>2.185132e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ft</td>\n",
       "      <td>2.033015e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fg</td>\n",
       "      <td>1.806852e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>x2p</td>\n",
       "      <td>1.553230e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>x3p</td>\n",
       "      <td>1.323455e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>sos</td>\n",
       "      <td>1.129936e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>orb</td>\n",
       "      <td>9.845280e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>x2p_percent</td>\n",
       "      <td>7.137697e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>tov_percent</td>\n",
       "      <td>6.072357e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>g</td>\n",
       "      <td>5.640987e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>x3pa</td>\n",
       "      <td>2.615296e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>n_rtg</td>\n",
       "      <td>2.280150e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>e_fg_percent_x</td>\n",
       "      <td>2.246846e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>tov</td>\n",
       "      <td>1.264480e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>age</td>\n",
       "      <td>1.258428e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>o_rtg</td>\n",
       "      <td>9.921903e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>mov</td>\n",
       "      <td>9.018780e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>pos</td>\n",
       "      <td>3.774605e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>x3p_percent</td>\n",
       "      <td>3.489269e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>x3p_ar</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>season</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>experience</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>pace</td>\n",
       "      <td>-1.330482e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>orb_percent</td>\n",
       "      <td>-6.975723e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>d_rtg</td>\n",
       "      <td>-3.132425e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ft_fga</td>\n",
       "      <td>-3.777677e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ft_percent</td>\n",
       "      <td>-1.546946e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ts_percent</td>\n",
       "      <td>-1.853738e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>pl</td>\n",
       "      <td>-2.281866e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ast</td>\n",
       "      <td>-3.105890e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gs</td>\n",
       "      <td>-4.621485e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>x2pa</td>\n",
       "      <td>-5.544221e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>f_tr</td>\n",
       "      <td>-7.456556e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>pf</td>\n",
       "      <td>-7.560872e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>stl</td>\n",
       "      <td>-8.424405e-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>blk</td>\n",
       "      <td>-1.009458e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>srs</td>\n",
       "      <td>-1.135206e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>pw</td>\n",
       "      <td>-1.377990e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>w</td>\n",
       "      <td>-4.399047e-02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               prd          test\n",
       "27             pts  2.335398e-01\n",
       "17             fta  5.981949e-02\n",
       "8       fg_percent  5.340742e-02\n",
       "29               l  4.948543e-02\n",
       "21             trb  4.088631e-02\n",
       "46            team  3.834525e-02\n",
       "7              fga  3.322384e-02\n",
       "5               mp  2.356932e-02\n",
       "20             drb  2.185132e-02\n",
       "16              ft  2.033015e-02\n",
       "6               fg  1.806852e-02\n",
       "12             x2p  1.553230e-02\n",
       "9              x3p  1.323455e-02\n",
       "33             sos  1.129936e-02\n",
       "19             orb  9.845280e-03\n",
       "14     x2p_percent  7.137697e-03\n",
       "42     tov_percent  6.072357e-03\n",
       "3                g  5.640987e-03\n",
       "10            x3pa  2.615296e-03\n",
       "37           n_rtg  2.280150e-03\n",
       "15  e_fg_percent_x  2.246846e-03\n",
       "25             tov  1.264480e-03\n",
       "1              age  1.258428e-03\n",
       "35           o_rtg  9.921903e-04\n",
       "32             mov  9.018780e-04\n",
       "45             pos  3.774605e-04\n",
       "11     x3p_percent  3.489269e-05\n",
       "40          x3p_ar  0.000000e+00\n",
       "0           season  0.000000e+00\n",
       "2       experience  0.000000e+00\n",
       "38            pace -1.330482e-07\n",
       "43     orb_percent -6.975723e-05\n",
       "36           d_rtg -3.132425e-04\n",
       "44          ft_fga -3.777677e-04\n",
       "18      ft_percent -1.546946e-03\n",
       "41      ts_percent -1.853738e-03\n",
       "31              pl -2.281866e-03\n",
       "22             ast -3.105890e-03\n",
       "4               gs -4.621485e-03\n",
       "13            x2pa -5.544221e-03\n",
       "39            f_tr -7.456556e-03\n",
       "26              pf -7.560872e-03\n",
       "23             stl -8.424405e-03\n",
       "24             blk -1.009458e-02\n",
       "34             srs -1.135206e-02\n",
       "30              pw -1.377990e-02\n",
       "28               w -4.399047e-02"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_imptnce\n",
    "#some important features are weighted very very low on the testing set\n",
    "#Win(w), percent_win(pw), steal, block, assist, game_start(gs) among others are negative for the model\n",
    "\n",
    "#what can be the correction to assign proper weight to features that influence the Target positively or negatively??\n",
    "#Monotonic Constraints!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "8d916e6a-ef6d-42fb-b458-f3ea63fbac50",
   "metadata": {},
   "outputs": [],
   "source": [
    "top_features_training = train_imptnce.head(20)\n",
    "top_features_testing = test_imptnce.head(20)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "e8858ef5-9dde-4006-b056-0d5397d25dc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "#visualising important features during training and testing\n",
    "\n",
    "plt.figure(figsize = (8,5))\n",
    "plt.bar(x=top_features_training['prd'], height= top_features_training['train'])\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Permutation Feature Importance on Training Set')\n",
    "plt.xlabel('Features')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a8e9f438-ebe0-4f52-810e-e95c9036f884",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8,5))\n",
    "plt.bar(x=top_features_testing['prd'], height= top_features_testing['test'])\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Permutation Feature Importance on Test Set')\n",
    "plt.xlabel('Features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "5b5c4bfb-7a48-4ee1-9b4d-710f6766ba0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "least_features_train = train_imptnce.tail(20)\n",
    "least_features_test = test_imptnce.tail(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "8a6c22a3-f8f0-4c5f-a52f-6ec08cb06e0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualising the least performing features on training and test set\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, layout='constrained', figsize=(12,5))\n",
    "\n",
    "ax1.bar(x=least_features_train['prd'], height=least_features_train['train'])\n",
    "ax1.set_title(\"Least Permutated Features on Training Set\")\n",
    "ax1.set_xlabel(\"Features\")\n",
    "\n",
    "\n",
    "ax2.bar(x=least_features_test['prd'], height= least_features_test['test'])\n",
    "ax2.set_title(\"Least Permutated Features on Testing Set\")\n",
    "ax2.set_xlabel(\"Features\")\n",
    "\n",
    "#slant the xticks on both axes\n",
    "for i, ax in enumerate([ax1, ax2]):\n",
    "    ax.set_xticks(ax.get_xticks()) # setting the ticks first before..\n",
    "    ax.set_xticklabels(ax.get_xticklabels(), rotation=45)  #x_ticklabel modifications\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "644859b5-c1f6-4f7d-88c4-1607266ed570",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Axes(0.044491,0.235203;0.449311x0.711796)\n",
      "Axes(0.547216,0.235203;0.449311x0.711796)\n"
     ]
    }
   ],
   "source": [
    "for i, ax in enumerate([ax1, ax2]):\n",
    "    print(ax)\n",
    "\n",
    "#why did the xtick_rotation only app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d9b222e-168c-4a90-bcd1-ee71630b58ff",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2f66d193-acda-4ecc-8b3f-7a606aa8aca0",
   "metadata": {},
   "source": [
    "FEATURE SELECTION ON THE MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ccf4c520-c19b-44e9-8b53-cd524a90f6a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Incomplete Procedure: still needs work\n",
    "\n",
    "from sklearn.feature_selection import SelectKBest,f_regression, RFECV\n",
    "from sklearn.model_selection import RepeatedKFold\n",
    "from sklearn.pipeline import make_pipeline, Pipeline\n",
    "from sklearn.svm import LinearSVR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "bdb66b4d-7cfc-417e-b31b-2fe63d682ea2",
   "metadata": {},
   "outputs": [],
   "source": [
    "one_hot = OneHotEncoder(sparse_output=False, handle_unknown=\"ignore\")\n",
    "\n",
    "preprocess = make_column_transformer(\n",
    "    (one_hot, ['pos', 'team']),\n",
    "    remainder=\"passthrough\"\n",
    ")\n",
    "select = SelectKBest(f_regression, k=25)\n",
    "\n",
    "hstg = HistGradientBoostingRegressor(max_iter=150, max_depth=5, random_state=42)\n",
    "\n",
    "pipe = make_pipeline(\n",
    "    preprocess,\n",
    "    select,\n",
    "    hstg\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "228eb3f4-470a-4637-916b-49555c07bb58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-6 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-6 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-6 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-6 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-6 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-6 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-6 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-6 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-6 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-6 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-6 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-6\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;selectkbest&#x27;,\n",
       "                 SelectKBest(k=25,\n",
       "                             score_func=&lt;function f_regression at 0x0000024EA1229080&gt;)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" ><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;selectkbest&#x27;,\n",
       "                 SelectKBest(k=25,\n",
       "                             score_func=&lt;function f_regression at 0x0000024EA1229080&gt;)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" ><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;columntransformer: ColumnTransformer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content \"><pre>ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                 OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                               sparse_output=False),\n",
       "                                 [&#x27;pos&#x27;, &#x27;team&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-17\" type=\"checkbox\" ><label for=\"sk-estimator-id-17\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">onehotencoder</label><div class=\"sk-toggleable__content \"><pre>[&#x27;pos&#x27;, &#x27;team&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" ><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content \"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;, sparse_output=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-19\" type=\"checkbox\" ><label for=\"sk-estimator-id-19\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">remainder</label><div class=\"sk-toggleable__content \"><pre></pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-20\" type=\"checkbox\" ><label for=\"sk-estimator-id-20\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">passthrough</label><div class=\"sk-toggleable__content \"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-21\" type=\"checkbox\" ><label for=\"sk-estimator-id-21\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;SelectKBest<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_selection.SelectKBest.html\">?<span>Documentation for SelectKBest</span></a></label><div class=\"sk-toggleable__content \"><pre>SelectKBest(k=25, score_func=&lt;function f_regression at 0x0000024EA1229080&gt;)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-22\" type=\"checkbox\" ><label for=\"sk-estimator-id-22\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content \"><pre>HistGradientBoostingRegressor(max_depth=5, max_iter=150, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore',\n",
       "                                                                sparse_output=False),\n",
       "                                                  ['pos', 'team'])])),\n",
       "                ('selectkbest',\n",
       "                 SelectKBest(k=25,\n",
       "                             score_func=<function f_regression at 0x0000024EA1229080>)),\n",
       "                ('histgradientboostingregressor',\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "8a78ac22-d4cb-4ad3-8e5b-526371dfa2d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\compose\\_column_transformer.py:1623: FutureWarning: \n",
      "The format of the columns of the 'remainder' transformer in ColumnTransformer.transformers_ will change in version 1.7 to match the format of the other transformers.\n",
      "At the moment the remainder columns are stored as indices (of type int). With the same ColumnTransformer configuration, in the future they will be stored as column names (of type str).\n",
      "To use the new behavior now and suppress this warning, use ColumnTransformer(force_int_remainder_cols=False).\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-7 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-7 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-7 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-7 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-7 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-7 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-7 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-7 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-7 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-7 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-7 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-7 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-7 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-7\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;selectkbest&#x27;,\n",
       "                 SelectKBest(k=25,\n",
       "                             score_func=&lt;function f_regression at 0x0000024EA1229080&gt;)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-23\" type=\"checkbox\" ><label for=\"sk-estimator-id-23\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;selectkbest&#x27;,\n",
       "                 SelectKBest(k=25,\n",
       "                             score_func=&lt;function f_regression at 0x0000024EA1229080&gt;)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-24\" type=\"checkbox\" ><label for=\"sk-estimator-id-24\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;columntransformer: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                 OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                               sparse_output=False),\n",
       "                                 [&#x27;pos&#x27;, &#x27;team&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-25\" type=\"checkbox\" ><label for=\"sk-estimator-id-25\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">onehotencoder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;pos&#x27;, &#x27;team&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-26\" type=\"checkbox\" ><label for=\"sk-estimator-id-26\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;, sparse_output=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-27\" type=\"checkbox\" ><label for=\"sk-estimator-id-27\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;season&#x27;, &#x27;age&#x27;, &#x27;experience&#x27;, &#x27;g&#x27;, &#x27;gs&#x27;, &#x27;mp&#x27;, &#x27;fg&#x27;, &#x27;fga&#x27;, &#x27;fg_percent&#x27;, &#x27;x3p&#x27;, &#x27;x3pa&#x27;, &#x27;x3p_percent&#x27;, &#x27;x2p&#x27;, &#x27;x2pa&#x27;, &#x27;x2p_percent&#x27;, &#x27;e_fg_percent_x&#x27;, &#x27;ft&#x27;, &#x27;fta&#x27;, &#x27;ft_percent&#x27;, &#x27;orb&#x27;, &#x27;drb&#x27;, &#x27;trb&#x27;, &#x27;ast&#x27;, &#x27;stl&#x27;, &#x27;blk&#x27;, &#x27;tov&#x27;, &#x27;pf&#x27;, &#x27;pts&#x27;, &#x27;w&#x27;, &#x27;l&#x27;, &#x27;pw&#x27;, &#x27;pl&#x27;, &#x27;mov&#x27;, &#x27;sos&#x27;, &#x27;srs&#x27;, &#x27;o_rtg&#x27;, &#x27;d_rtg&#x27;, &#x27;n_rtg&#x27;, &#x27;pace&#x27;, &#x27;f_tr&#x27;, &#x27;x3p_ar&#x27;, &#x27;ts_percent&#x27;, &#x27;tov_percent&#x27;, &#x27;orb_percent&#x27;, &#x27;ft_fga&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-28\" type=\"checkbox\" ><label for=\"sk-estimator-id-28\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-29\" type=\"checkbox\" ><label for=\"sk-estimator-id-29\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;SelectKBest<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_selection.SelectKBest.html\">?<span>Documentation for SelectKBest</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>SelectKBest(k=25, score_func=&lt;function f_regression at 0x0000024EA1229080&gt;)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-30\" type=\"checkbox\" ><label for=\"sk-estimator-id-30\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(max_depth=5, max_iter=150, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore',\n",
       "                                                                sparse_output=False),\n",
       "                                                  ['pos', 'team'])])),\n",
       "                ('selectkbest',\n",
       "                 SelectKBest(k=25,\n",
       "                             score_func=<function f_regression at 0x0000024EA1229080>)),\n",
       "                ('histgradientboostingregressor',\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.fit(train[predictors], train['share'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "9ac60df7-735c-45b0-9b13-e02e4da36d31",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['onehotencoder__pos_C', 'onehotencoder__pos_C-PF',\n",
       "       'onehotencoder__pos_PF', 'onehotencoder__pos_PF-C',\n",
       "       'onehotencoder__pos_PF-SF', 'onehotencoder__pos_PG',\n",
       "       'onehotencoder__pos_PG-SF', 'onehotencoder__pos_PG-SG',\n",
       "       'onehotencoder__pos_SF', 'onehotencoder__pos_SF-C',\n",
       "       'onehotencoder__pos_SF-PF', 'onehotencoder__pos_SF-SG',\n",
       "       'onehotencoder__pos_SG', 'onehotencoder__pos_SG-PF',\n",
       "       'onehotencoder__pos_SG-PG', 'onehotencoder__pos_SG-PG-SF',\n",
       "       'onehotencoder__pos_SG-SF', 'onehotencoder__team_Atlanta Hawks',\n",
       "       'onehotencoder__team_Boston Celtics',\n",
       "       'onehotencoder__team_Brooklyn Nets',\n",
       "       'onehotencoder__team_Charlotte Bobcats',\n",
       "       'onehotencoder__team_Charlotte Hornets',\n",
       "       'onehotencoder__team_Chicago Bulls',\n",
       "       'onehotencoder__team_Cleveland Cavaliers',\n",
       "       'onehotencoder__team_Dallas Mavericks',\n",
       "       'onehotencoder__team_Denver Nuggets',\n",
       "       'onehotencoder__team_Detroit Pistons',\n",
       "       'onehotencoder__team_Golden State Warriors',\n",
       "       'onehotencoder__team_Houston Rockets',\n",
       "       'onehotencoder__team_Indiana Pacers',\n",
       "       'onehotencoder__team_Los Angeles Clippers',\n",
       "       'onehotencoder__team_Los Angeles Lakers',\n",
       "       'onehotencoder__team_Memphis Grizzlies',\n",
       "       'onehotencoder__team_Miami Heat',\n",
       "       'onehotencoder__team_Milwaukee Bucks',\n",
       "       'onehotencoder__team_Minnesota Timberwolves',\n",
       "       'onehotencoder__team_New Jersey Nets',\n",
       "       'onehotencoder__team_New Orleans Hornets',\n",
       "       'onehotencoder__team_New Orleans Pelicans',\n",
       "       'onehotencoder__team_New Orleans/Oklahoma City Hornets',\n",
       "       'onehotencoder__team_New York Knicks',\n",
       "       'onehotencoder__team_Oklahoma City Thunder',\n",
       "       'onehotencoder__team_Orlando Magic',\n",
       "       'onehotencoder__team_Philadelphia 76ers',\n",
       "       'onehotencoder__team_Phoenix Suns',\n",
       "       'onehotencoder__team_Portland Trail Blazers',\n",
       "       'onehotencoder__team_Sacramento Kings',\n",
       "       'onehotencoder__team_San Antonio Spurs',\n",
       "       'onehotencoder__team_Seattle SuperSonics',\n",
       "       'onehotencoder__team_Toronto Raptors',\n",
       "       'onehotencoder__team_Utah Jazz',\n",
       "       'onehotencoder__team_Vancouver Grizzlies',\n",
       "       'onehotencoder__team_Washington Bullets',\n",
       "       'onehotencoder__team_Washington Wizards', 'remainder__season',\n",
       "       'remainder__age', 'remainder__experience', 'remainder__g',\n",
       "       'remainder__gs', 'remainder__mp', 'remainder__fg',\n",
       "       'remainder__fga', 'remainder__fg_percent', 'remainder__x3p',\n",
       "       'remainder__x3pa', 'remainder__x3p_percent', 'remainder__x2p',\n",
       "       'remainder__x2pa', 'remainder__x2p_percent',\n",
       "       'remainder__e_fg_percent_x', 'remainder__ft', 'remainder__fta',\n",
       "       'remainder__ft_percent', 'remainder__orb', 'remainder__drb',\n",
       "       'remainder__trb', 'remainder__ast', 'remainder__stl',\n",
       "       'remainder__blk', 'remainder__tov', 'remainder__pf',\n",
       "       'remainder__pts', 'remainder__w', 'remainder__l', 'remainder__pw',\n",
       "       'remainder__pl', 'remainder__mov', 'remainder__sos',\n",
       "       'remainder__srs', 'remainder__o_rtg', 'remainder__d_rtg',\n",
       "       'remainder__n_rtg', 'remainder__pace', 'remainder__f_tr',\n",
       "       'remainder__x3p_ar', 'remainder__ts_percent',\n",
       "       'remainder__tov_percent', 'remainder__orb_percent',\n",
       "       'remainder__ft_fga'], dtype=object)"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe[:-1].get_feature_names_out()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "b2ba2067-e788-421a-bbe0-e4ebe867aaea",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.inspection import permutation_importance\n",
    "def find_permutation(model, predictors, target, column_name):\n",
    "    train_impt = permutation_importance(\n",
    "    model, predictors, target, random_state = 0, n_repeats = 42, n_jobs = 2\n",
    "    )\n",
    "    \n",
    "    train_num = train_impt['importances_mean'].reshape(-1,1)\n",
    "    train_num = pd.DataFrame(train_num, columns = column_name)\n",
    "\n",
    "    features = predictors.columns\n",
    "    features = pd.DataFrame(features, columns = ['features'])\n",
    "\n",
    "    train_features = pd.concat([features, train_num], axis =1)\n",
    "    top_train_features = train_features.sort_values(column_name, ascending=False).head(20)\n",
    "    least_train_features = train_features.sort_values(column_name, ascending=False).tail(20)\n",
    "\n",
    "    return top_train_features, least_train_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "80907cf8-c6d1-42b9-9d34-c7336a190776",
   "metadata": {},
   "outputs": [],
   "source": [
    "top_features_kbest, least_features_kbest = find_permutation(\n",
    "    pipe, train[predictors], train['share'], ['train'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "bc23d0e2-bee3-4680-bc99-59e6d2b03644",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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>features</th>\n",
       "      <th>train</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>pts</td>\n",
       "      <td>0.363308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>l</td>\n",
       "      <td>0.153988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fg</td>\n",
       "      <td>0.105780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>fta</td>\n",
       "      <td>0.071130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ast</td>\n",
       "      <td>0.068305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>srs</td>\n",
       "      <td>0.033707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mp</td>\n",
       "      <td>0.029296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>w</td>\n",
       "      <td>0.025423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ft</td>\n",
       "      <td>0.019626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>drb</td>\n",
       "      <td>0.017364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>trb</td>\n",
       "      <td>0.016539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>g</td>\n",
       "      <td>0.012328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>pf</td>\n",
       "      <td>0.011314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>blk</td>\n",
       "      <td>0.011213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>fg_percent</td>\n",
       "      <td>0.010226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>pl</td>\n",
       "      <td>0.010072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>tov</td>\n",
       "      <td>0.009496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>x2p</td>\n",
       "      <td>0.008738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>f_tr</td>\n",
       "      <td>0.008678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>x2pa</td>\n",
       "      <td>0.008255</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      features     train\n",
       "27         pts  0.363308\n",
       "29           l  0.153988\n",
       "6           fg  0.105780\n",
       "17         fta  0.071130\n",
       "22         ast  0.068305\n",
       "34         srs  0.033707\n",
       "5           mp  0.029296\n",
       "28           w  0.025423\n",
       "16          ft  0.019626\n",
       "20         drb  0.017364\n",
       "21         trb  0.016539\n",
       "3            g  0.012328\n",
       "26          pf  0.011314\n",
       "24         blk  0.011213\n",
       "8   fg_percent  0.010226\n",
       "31          pl  0.010072\n",
       "25         tov  0.009496\n",
       "12         x2p  0.008738\n",
       "39        f_tr  0.008678\n",
       "13        x2pa  0.008255"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_features_kbest\n",
    "#selckBest together with HistGradientBoosting picks more \"important Features\" on training set\n",
    "#Overall it is almost the same pick as the Orginal Histogram Model (without SelectKBest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "f3f6ff5b-b6fa-4e6d-9670-5d7fb0d67a24",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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>features</th>\n",
       "      <th>train</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>o_rtg</td>\n",
       "      <td>0.005123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>orb_percent</td>\n",
       "      <td>0.004513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>pace</td>\n",
       "      <td>0.004129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gs</td>\n",
       "      <td>0.002896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>tov_percent</td>\n",
       "      <td>0.002785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>x3pa</td>\n",
       "      <td>0.002752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ts_percent</td>\n",
       "      <td>0.002302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>pw</td>\n",
       "      <td>0.002244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>n_rtg</td>\n",
       "      <td>0.001655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>x3p</td>\n",
       "      <td>0.001563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>e_fg_percent_x</td>\n",
       "      <td>0.001412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fga</td>\n",
       "      <td>0.001192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>orb</td>\n",
       "      <td>0.001155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>sos</td>\n",
       "      <td>0.001095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>x3p_percent</td>\n",
       "      <td>0.000479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>age</td>\n",
       "      <td>0.000169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>team</td>\n",
       "      <td>0.000128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>season</td>\n",
       "      <td>0.000110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>experience</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>pos</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          features     train\n",
       "35           o_rtg  0.005123\n",
       "43     orb_percent  0.004513\n",
       "38            pace  0.004129\n",
       "4               gs  0.002896\n",
       "42     tov_percent  0.002785\n",
       "10            x3pa  0.002752\n",
       "41      ts_percent  0.002302\n",
       "30              pw  0.002244\n",
       "37           n_rtg  0.001655\n",
       "9              x3p  0.001563\n",
       "15  e_fg_percent_x  0.001412\n",
       "7              fga  0.001192\n",
       "19             orb  0.001155\n",
       "33             sos  0.001095\n",
       "11     x3p_percent  0.000479\n",
       "1              age  0.000169\n",
       "46            team  0.000128\n",
       "0           season  0.000110\n",
       "2       experience  0.000000\n",
       "45             pos  0.000000"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "least_features_kbest\n",
    "#Position(pos), team and Experience do not contribute to the models predictions !!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "b33fe088-1490-4ffd-a3bd-8c9fa99c2490",
   "metadata": {},
   "outputs": [],
   "source": [
    "#another feature selection method with RFECV, lASSO AND HST`\n",
    "cv = RepeatedKFold(n_splits =2, n_repeats =5, random_state=42)\n",
    "\n",
    "one_hot = OneHotEncoder(sparse_output=False, handle_unknown=\"ignore\")\n",
    "\n",
    "preprocess = make_column_transformer(\n",
    "    (one_hot, ['pos', 'team']),\n",
    "    remainder=\"passthrough\", \n",
    "    force_int_remainder_cols =False\n",
    ")\n",
    "\n",
    "svr = LinearSVR(random_state=42)\n",
    "\n",
    "rfe = RFECV(svr, min_features_to_select=25, cv=cv, n_jobs=2) #use a different estimator\n",
    "pipe_1 = make_pipeline(\n",
    "    preprocess,\n",
    "    rfe,\n",
    "    hstg\n",
    ")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "819f7a9b-3fa2-42d8-be96-19fc965a69ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-47 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-47 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-47 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-47 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-47 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-47 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-47 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-47 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-47 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-47 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-47 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-47 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-47 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-47 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-47 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-47 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-47 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-47 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-47 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-47\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "      estimator=LinearSVR(random_state=42), min_features_to_select=25,\n",
       "      n_jobs=2)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-261\" type=\"checkbox\" ><label for=\"sk-estimator-id-261\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;RFECV<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_selection.RFECV.html\">?<span>Documentation for RFECV</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "      estimator=LinearSVR(random_state=42), min_features_to_select=25,\n",
       "      n_jobs=2)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-262\" type=\"checkbox\" ><label for=\"sk-estimator-id-262\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">estimator: LinearSVR</label><div class=\"sk-toggleable__content \"><pre>LinearSVR(random_state=42)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-263\" type=\"checkbox\" ><label for=\"sk-estimator-id-263\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;LinearSVR<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.LinearSVR.html\">?<span>Documentation for LinearSVR</span></a></label><div class=\"sk-toggleable__content \"><pre>LinearSVR(random_state=42)</pre></div> </div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "      estimator=LinearSVR(random_state=42), min_features_to_select=25,\n",
       "      n_jobs=2)"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "6be30c8d-0435-46e4-979e-42feee412987",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-48 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-48 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-48 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-48 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-48 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-48 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-48 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-48 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-48 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-48 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-48 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-48 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-48 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-48 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-48 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-48 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-48 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-48 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-48 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-48\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;rfecv&#x27;,\n",
       "                 RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "                       estimator=LinearSVR(random_state=42),\n",
       "                       min_features_to_select=25, n_jobs=2)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-264\" type=\"checkbox\" ><label for=\"sk-estimator-id-264\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;rfecv&#x27;,\n",
       "                 RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "                       estimator=LinearSVR(random_state=42),\n",
       "                       min_features_to_select=25, n_jobs=2)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-265\" type=\"checkbox\" ><label for=\"sk-estimator-id-265\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;columntransformer: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                 OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                               sparse_output=False),\n",
       "                                 [&#x27;pos&#x27;, &#x27;team&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-266\" type=\"checkbox\" ><label for=\"sk-estimator-id-266\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">onehotencoder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;pos&#x27;, &#x27;team&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-267\" type=\"checkbox\" ><label for=\"sk-estimator-id-267\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;, sparse_output=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-268\" type=\"checkbox\" ><label for=\"sk-estimator-id-268\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre></pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-269\" type=\"checkbox\" ><label for=\"sk-estimator-id-269\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-270\" type=\"checkbox\" ><label for=\"sk-estimator-id-270\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;rfecv: RFECV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_selection.RFECV.html\">?<span>Documentation for rfecv: RFECV</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "      estimator=LinearSVR(random_state=42), min_features_to_select=25,\n",
       "      n_jobs=2)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-271\" type=\"checkbox\" ><label for=\"sk-estimator-id-271\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: LinearSVR</label><div class=\"sk-toggleable__content fitted\"><pre>LinearSVR(random_state=42)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-272\" type=\"checkbox\" ><label for=\"sk-estimator-id-272\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearSVR<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.LinearSVR.html\">?<span>Documentation for LinearSVR</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearSVR(random_state=42)</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-273\" type=\"checkbox\" ><label for=\"sk-estimator-id-273\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(max_depth=5, max_iter=150, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore',\n",
       "                                                                sparse_output=False),\n",
       "                                                  ['pos', 'team'])])),\n",
       "                ('rfecv',\n",
       "                 RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "                       estimator=LinearSVR(random_state=42),\n",
       "                       min_features_to_select=25, n_jobs=2)),\n",
       "                ('histgradientboostingregressor',\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "dcbc1c54-1c28-466c-8224-8a5bd33e5c8e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\svm\\_base.py:1235: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-49 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-49 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-49 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-49 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-49 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-49 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-49 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-49 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-49 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-49 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-49 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-49 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-49 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-49 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-49 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-49 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-49 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-49 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-49 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-49\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;rfecv&#x27;,\n",
       "                 RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "                       estimator=LinearSVR(random_state=42),\n",
       "                       min_features_to_select=25, n_jobs=2)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-274\" type=\"checkbox\" ><label for=\"sk-estimator-id-274\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;rfecv&#x27;,\n",
       "                 RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "                       estimator=LinearSVR(random_state=42),\n",
       "                       min_features_to_select=25, n_jobs=2)),\n",
       "                (&#x27;histgradientboostingregressor&#x27;,\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-275\" type=\"checkbox\" ><label for=\"sk-estimator-id-275\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;columntransformer: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(force_int_remainder_cols=False, remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                 OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                               sparse_output=False),\n",
       "                                 [&#x27;pos&#x27;, &#x27;team&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-276\" type=\"checkbox\" ><label for=\"sk-estimator-id-276\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">onehotencoder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;pos&#x27;, &#x27;team&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-277\" type=\"checkbox\" ><label for=\"sk-estimator-id-277\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;, sparse_output=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-278\" type=\"checkbox\" ><label for=\"sk-estimator-id-278\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;season&#x27;, &#x27;age&#x27;, &#x27;experience&#x27;, &#x27;g&#x27;, &#x27;gs&#x27;, &#x27;mp&#x27;, &#x27;fg&#x27;, &#x27;fga&#x27;, &#x27;fg_percent&#x27;, &#x27;x3p&#x27;, &#x27;x3pa&#x27;, &#x27;x3p_percent&#x27;, &#x27;x2p&#x27;, &#x27;x2pa&#x27;, &#x27;x2p_percent&#x27;, &#x27;e_fg_percent_x&#x27;, &#x27;ft&#x27;, &#x27;fta&#x27;, &#x27;ft_percent&#x27;, &#x27;orb&#x27;, &#x27;drb&#x27;, &#x27;trb&#x27;, &#x27;ast&#x27;, &#x27;stl&#x27;, &#x27;blk&#x27;, &#x27;tov&#x27;, &#x27;pf&#x27;, &#x27;pts&#x27;, &#x27;w&#x27;, &#x27;l&#x27;, &#x27;pw&#x27;, &#x27;pl&#x27;, &#x27;mov&#x27;, &#x27;sos&#x27;, &#x27;srs&#x27;, &#x27;o_rtg&#x27;, &#x27;d_rtg&#x27;, &#x27;n_rtg&#x27;, &#x27;pace&#x27;, &#x27;f_tr&#x27;, &#x27;x3p_ar&#x27;, &#x27;ts_percent&#x27;, &#x27;tov_percent&#x27;, &#x27;orb_percent&#x27;, &#x27;ft_fga&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-279\" type=\"checkbox\" ><label for=\"sk-estimator-id-279\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-280\" type=\"checkbox\" ><label for=\"sk-estimator-id-280\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;rfecv: RFECV<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.feature_selection.RFECV.html\">?<span>Documentation for rfecv: RFECV</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "      estimator=LinearSVR(random_state=42), min_features_to_select=25,\n",
       "      n_jobs=2)</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-281\" type=\"checkbox\" ><label for=\"sk-estimator-id-281\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">estimator: LinearSVR</label><div class=\"sk-toggleable__content fitted\"><pre>LinearSVR(random_state=42)</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-282\" type=\"checkbox\" ><label for=\"sk-estimator-id-282\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LinearSVR<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.LinearSVR.html\">?<span>Documentation for LinearSVR</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LinearSVR(random_state=42)</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-283\" type=\"checkbox\" ><label for=\"sk-estimator-id-283\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;HistGradientBoostingRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html\">?<span>Documentation for HistGradientBoostingRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>HistGradientBoostingRegressor(max_depth=5, max_iter=150, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(force_int_remainder_cols=False,\n",
       "                                   remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore',\n",
       "                                                                sparse_output=False),\n",
       "                                                  ['pos', 'team'])])),\n",
       "                ('rfecv',\n",
       "                 RFECV(cv=RepeatedKFold(n_repeats=5, n_splits=2, random_state=42),\n",
       "                       estimator=LinearSVR(random_state=42),\n",
       "                       min_features_to_select=25, n_jobs=2)),\n",
       "                ('histgradientboostingregressor',\n",
       "                 HistGradientBoostingRegressor(max_depth=5, max_iter=150,\n",
       "                                               random_state=42))])"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe_1.fit(train[predictors], train['share'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "2eab5457-5b84-473e-94f1-2d2e401c496f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['onehotencoder__pos_C', 'onehotencoder__pos_PF',\n",
       "       'onehotencoder__pos_PF-SF', 'onehotencoder__pos_PG',\n",
       "       'onehotencoder__pos_SF', 'onehotencoder__pos_SG',\n",
       "       'onehotencoder__pos_SG-SF', 'onehotencoder__team_Atlanta Hawks',\n",
       "       'onehotencoder__team_Boston Celtics',\n",
       "       'onehotencoder__team_Brooklyn Nets',\n",
       "       'onehotencoder__team_Charlotte Hornets',\n",
       "       'onehotencoder__team_Chicago Bulls',\n",
       "       'onehotencoder__team_Denver Nuggets',\n",
       "       'onehotencoder__team_Houston Rockets',\n",
       "       'onehotencoder__team_Indiana Pacers',\n",
       "       'onehotencoder__team_Los Angeles Clippers',\n",
       "       'onehotencoder__team_Los Angeles Lakers',\n",
       "       'onehotencoder__team_Memphis Grizzlies',\n",
       "       'onehotencoder__team_Miami Heat',\n",
       "       'onehotencoder__team_Minnesota Timberwolves',\n",
       "       'onehotencoder__team_New Jersey Nets',\n",
       "       'onehotencoder__team_New Orleans Hornets',\n",
       "       'onehotencoder__team_New York Knicks',\n",
       "       'onehotencoder__team_Oklahoma City Thunder',\n",
       "       'onehotencoder__team_Orlando Magic',\n",
       "       'onehotencoder__team_Philadelphia 76ers',\n",
       "       'onehotencoder__team_Portland Trail Blazers',\n",
       "       'onehotencoder__team_Sacramento Kings',\n",
       "       'onehotencoder__team_San Antonio Spurs',\n",
       "       'onehotencoder__team_Seattle SuperSonics',\n",
       "       'onehotencoder__team_Utah Jazz',\n",
       "       'onehotencoder__team_Vancouver Grizzlies', 'remainder__age',\n",
       "       'remainder__gs', 'remainder__fg', 'remainder__fga',\n",
       "       'remainder__fg_percent', 'remainder__x3p_percent',\n",
       "       'remainder__x2p', 'remainder__x2pa', 'remainder__x2p_percent',\n",
       "       'remainder__e_fg_percent_x', 'remainder__ft', 'remainder__fta',\n",
       "       'remainder__ft_percent', 'remainder__orb', 'remainder__drb',\n",
       "       'remainder__ast', 'remainder__stl', 'remainder__blk',\n",
       "       'remainder__tov', 'remainder__pf', 'remainder__pl',\n",
       "       'remainder__mov', 'remainder__sos', 'remainder__srs',\n",
       "       'remainder__o_rtg', 'remainder__n_rtg', 'remainder__pace',\n",
       "       'remainder__tov_percent'], dtype=object)"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe_1[:-1].get_feature_names_out()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "c4a9eb7c-b7a3-49d1-9a2d-2d87dd4f9a56",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Recursive Elimination, Features Importance\n",
    "\n",
    "top_features_rfe, least_features_rfe = find_permutation(\n",
    "    pipe_1, train[predictors], train['share'], ['train']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "f2b45b06-714a-4847-8437-6bafc347f7cc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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>features</th>\n",
       "      <th>train</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fg</td>\n",
       "      <td>0.399452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>fta</td>\n",
       "      <td>0.117355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ast</td>\n",
       "      <td>0.103265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>mov</td>\n",
       "      <td>0.079917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>pl</td>\n",
       "      <td>0.077286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ft</td>\n",
       "      <td>0.058387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gs</td>\n",
       "      <td>0.042168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>pf</td>\n",
       "      <td>0.040953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>drb</td>\n",
       "      <td>0.033872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>srs</td>\n",
       "      <td>0.032480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>blk</td>\n",
       "      <td>0.023088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>x2p</td>\n",
       "      <td>0.020723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>e_fg_percent_x</td>\n",
       "      <td>0.019313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>x2pa</td>\n",
       "      <td>0.017416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>tov</td>\n",
       "      <td>0.016034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fga</td>\n",
       "      <td>0.015589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>stl</td>\n",
       "      <td>0.013259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ft_percent</td>\n",
       "      <td>0.012180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>orb</td>\n",
       "      <td>0.011247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>o_rtg</td>\n",
       "      <td>0.009692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          features     train\n",
       "6               fg  0.399452\n",
       "17             fta  0.117355\n",
       "22             ast  0.103265\n",
       "32             mov  0.079917\n",
       "31              pl  0.077286\n",
       "16              ft  0.058387\n",
       "4               gs  0.042168\n",
       "26              pf  0.040953\n",
       "20             drb  0.033872\n",
       "34             srs  0.032480\n",
       "24             blk  0.023088\n",
       "12             x2p  0.020723\n",
       "15  e_fg_percent_x  0.019313\n",
       "13            x2pa  0.017416\n",
       "25             tov  0.016034\n",
       "7              fga  0.015589\n",
       "23             stl  0.013259\n",
       "18      ft_percent  0.012180\n",
       "19             orb  0.011247\n",
       "35           o_rtg  0.009692"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_features_rfe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "03876903-111f-41c1-82a3-0af23a34ed4a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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>features</th>\n",
       "      <th>train</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>team</td>\n",
       "      <td>0.001329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>age</td>\n",
       "      <td>0.000603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>pos</td>\n",
       "      <td>0.000380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>w</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>g</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ft_fga</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>orb_percent</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>experience</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>ts_percent</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>x3p_ar</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>f_tr</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mp</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>l</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>d_rtg</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>x3p</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>x3pa</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>trb</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>pts</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>pw</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>season</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       features     train\n",
       "46         team  0.001329\n",
       "1           age  0.000603\n",
       "45          pos  0.000380\n",
       "28            w  0.000000\n",
       "3             g  0.000000\n",
       "44       ft_fga  0.000000\n",
       "43  orb_percent  0.000000\n",
       "2    experience  0.000000\n",
       "41   ts_percent  0.000000\n",
       "40       x3p_ar  0.000000\n",
       "39         f_tr  0.000000\n",
       "5            mp  0.000000\n",
       "29            l  0.000000\n",
       "36        d_rtg  0.000000\n",
       "9           x3p  0.000000\n",
       "10         x3pa  0.000000\n",
       "21          trb  0.000000\n",
       "27          pts  0.000000\n",
       "30           pw  0.000000\n",
       "0        season  0.000000"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "least_features_rfe\n",
    "#points, won(w), experience and Percent_won(pw) do not contribute to the model's predictions at all!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6cbde956-867b-48f7-9628-80aab765f0d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#There is still works to do on the above filttered models\n",
    "#Backtesting the models, to find predictions and mean_error over the years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a1486a93-8e90-4220-bd47-2d99a9de1c09",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "01509e26-de3f-451a-b6d9-75d3b2bb8ee2",
   "metadata": {},
   "source": [
    "RANDOM FOREST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "749ce0d6-e8b4-4809-9c59-6c56d1b238cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#defining randomforest estimator\n",
    "from sklearn.compose import make_column_transformer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.pipeline import make_pipeline\n",
    "\n",
    "rdf = RandomForestRegressor(\n",
    "    n_estimators = 1000,\n",
    "    n_jobs = 2,\n",
    "    random_state = 42 \n",
    ")\n",
    "\n",
    "one_hot = OneHotEncoder(sparse_output=False, handle_unknown=\"ignore\")\n",
    "\n",
    "preprocess = make_column_transformer(\n",
    "    (one_hot, ['pos', 'team']),\n",
    "    remainder=\"passthrough\"\n",
    ")\n",
    "\n",
    "rf_pipe = make_pipeline(\n",
    "    preprocess,\n",
    "   rdf \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "441a735f-dcc7-4c88-be28-fe389ca8103d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-54 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-54 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-54 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-54 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-54 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-54 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-54 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-54 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-54 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-54 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-54 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-54 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-54 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-54 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-54 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-54 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-54 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-54 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-54 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-54\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;randomforestregressor&#x27;,\n",
       "                 RandomForestRegressor(n_estimators=1000, n_jobs=2,\n",
       "                                       random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-309\" type=\"checkbox\" ><label for=\"sk-estimator-id-309\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;randomforestregressor&#x27;,\n",
       "                 RandomForestRegressor(n_estimators=1000, n_jobs=2,\n",
       "                                       random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-310\" type=\"checkbox\" ><label for=\"sk-estimator-id-310\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;columntransformer: ColumnTransformer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content \"><pre>ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                 OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                               sparse_output=False),\n",
       "                                 [&#x27;pos&#x27;, &#x27;team&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-311\" type=\"checkbox\" ><label for=\"sk-estimator-id-311\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">onehotencoder</label><div class=\"sk-toggleable__content \"><pre>[&#x27;pos&#x27;, &#x27;team&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-312\" type=\"checkbox\" ><label for=\"sk-estimator-id-312\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content \"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;, sparse_output=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-313\" type=\"checkbox\" ><label for=\"sk-estimator-id-313\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">remainder</label><div class=\"sk-toggleable__content \"><pre></pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-314\" type=\"checkbox\" ><label for=\"sk-estimator-id-314\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">passthrough</label><div class=\"sk-toggleable__content \"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-315\" type=\"checkbox\" ><label for=\"sk-estimator-id-315\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;RandomForestRegressor<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html\">?<span>Documentation for RandomForestRegressor</span></a></label><div class=\"sk-toggleable__content \"><pre>RandomForestRegressor(n_estimators=1000, n_jobs=2, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore',\n",
       "                                                                sparse_output=False),\n",
       "                                                  ['pos', 'team'])])),\n",
       "                ('randomforestregressor',\n",
       "                 RandomForestRegressor(n_estimators=1000, n_jobs=2,\n",
       "                                       random_state=42))])"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_pipe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "caeea00a-2a6a-4602-8f31-db4a866107e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Hp Pc\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\compose\\_column_transformer.py:1623: FutureWarning: \n",
      "The format of the columns of the 'remainder' transformer in ColumnTransformer.transformers_ will change in version 1.7 to match the format of the other transformers.\n",
      "At the moment the remainder columns are stored as indices (of type int). With the same ColumnTransformer configuration, in the future they will be stored as column names (of type str).\n",
      "To use the new behavior now and suppress this warning, use ColumnTransformer(force_int_remainder_cols=False).\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-55 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-55 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-55 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-55 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-55 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-55 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-55 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-55 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-55 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-55 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-55 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-55 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-55 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-55 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-55 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-55 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-55 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-55 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-55 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-55\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;randomforestregressor&#x27;,\n",
       "                 RandomForestRegressor(n_estimators=1000, n_jobs=2,\n",
       "                                       random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-316\" type=\"checkbox\" ><label for=\"sk-estimator-id-316\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                                   transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                                                sparse_output=False),\n",
       "                                                  [&#x27;pos&#x27;, &#x27;team&#x27;])])),\n",
       "                (&#x27;randomforestregressor&#x27;,\n",
       "                 RandomForestRegressor(n_estimators=1000, n_jobs=2,\n",
       "                                       random_state=42))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-317\" type=\"checkbox\" ><label for=\"sk-estimator-id-317\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;columntransformer: ColumnTransformer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.compose.ColumnTransformer.html\">?<span>Documentation for columntransformer: ColumnTransformer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>ColumnTransformer(remainder=&#x27;passthrough&#x27;,\n",
       "                  transformers=[(&#x27;onehotencoder&#x27;,\n",
       "                                 OneHotEncoder(handle_unknown=&#x27;ignore&#x27;,\n",
       "                                               sparse_output=False),\n",
       "                                 [&#x27;pos&#x27;, &#x27;team&#x27;])])</pre></div> </div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-318\" type=\"checkbox\" ><label for=\"sk-estimator-id-318\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">onehotencoder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;pos&#x27;, &#x27;team&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-319\" type=\"checkbox\" ><label for=\"sk-estimator-id-319\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;OneHotEncoder<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.OneHotEncoder.html\">?<span>Documentation for OneHotEncoder</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;, sparse_output=False)</pre></div> </div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-320\" type=\"checkbox\" ><label for=\"sk-estimator-id-320\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">remainder</label><div class=\"sk-toggleable__content fitted\"><pre>[&#x27;season&#x27;, &#x27;age&#x27;, &#x27;experience&#x27;, &#x27;g&#x27;, &#x27;gs&#x27;, &#x27;mp&#x27;, &#x27;fg&#x27;, &#x27;fga&#x27;, &#x27;fg_percent&#x27;, &#x27;x3p&#x27;, &#x27;x3pa&#x27;, &#x27;x3p_percent&#x27;, &#x27;x2p&#x27;, &#x27;x2pa&#x27;, &#x27;x2p_percent&#x27;, &#x27;e_fg_percent_x&#x27;, &#x27;ft&#x27;, &#x27;fta&#x27;, &#x27;ft_percent&#x27;, &#x27;orb&#x27;, &#x27;drb&#x27;, &#x27;trb&#x27;, &#x27;ast&#x27;, &#x27;stl&#x27;, &#x27;blk&#x27;, &#x27;tov&#x27;, &#x27;pf&#x27;, &#x27;pts&#x27;, &#x27;w&#x27;, &#x27;l&#x27;, &#x27;pw&#x27;, &#x27;pl&#x27;, &#x27;mov&#x27;, &#x27;sos&#x27;, &#x27;srs&#x27;, &#x27;o_rtg&#x27;, &#x27;d_rtg&#x27;, &#x27;n_rtg&#x27;, &#x27;pace&#x27;, &#x27;f_tr&#x27;, &#x27;x3p_ar&#x27;, &#x27;ts_percent&#x27;, &#x27;tov_percent&#x27;, &#x27;orb_percent&#x27;, &#x27;ft_fga&#x27;]</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-321\" type=\"checkbox\" ><label for=\"sk-estimator-id-321\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">passthrough</label><div class=\"sk-toggleable__content fitted\"><pre>passthrough</pre></div> </div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-322\" type=\"checkbox\" ><label for=\"sk-estimator-id-322\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;RandomForestRegressor<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html\">?<span>Documentation for RandomForestRegressor</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestRegressor(n_estimators=1000, n_jobs=2, random_state=42)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore',\n",
       "                                                                sparse_output=False),\n",
       "                                                  ['pos', 'team'])])),\n",
       "                ('randomforestregressor',\n",
       "                 RandomForestRegressor(n_estimators=1000, n_jobs=2,\n",
       "                                       random_state=42))])"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_pipe.fit(train[predictors], train['share'])\n",
    "\n",
    "#contiues to raise error\n",
    "#TypeError: All estimators should implement fit and transform, or can be 'drop' or 'passthrough' specifiers. 'p' (type <class 'str'>) doesn't."
   ]
  }
 ],
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