1465 lines
384 KiB
Plaintext
1465 lines
384 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Imports"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"from sklearn.model_selection import train_test_split, StratifiedKFold, GridSearchCV\n",
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"from sklearn.metrics import confusion_matrix, mean_squared_error, mean_absolute_error, r2_score\n",
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"import xgboost\n",
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"import time\n",
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"from joblib import dump, load\n",
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"import os"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Load the data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_csv('final_data_new.csv')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Index(['minute', 'position_name', 'shot_body_part_name', 'shot_technique_name',\n",
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" 'shot_type_name', 'shot_first_time', 'shot_one_on_one',\n",
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" 'shot_aerial_won', 'shot_open_goal', 'shot_follows_dribble',\n",
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" 'shot_redirect', 'x1', 'y1', 'number_of_players_opponents',\n",
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" 'number_of_players_teammates', 'is_goal', 'angle', 'distance',\n",
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" 'x_player_opponent_Goalkeeper', 'x_player_opponent_8',\n",
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" 'x_player_opponent_1', 'x_player_opponent_2', 'x_player_opponent_3',\n",
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" 'x_player_teammate_1', 'x_player_opponent_4', 'x_player_opponent_5',\n",
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" 'x_player_opponent_6', 'x_player_teammate_2', 'x_player_opponent_9',\n",
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" 'x_player_opponent_10', 'x_player_opponent_11', 'x_player_teammate_3',\n",
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" 'x_player_teammate_4', 'x_player_teammate_5', 'x_player_teammate_6',\n",
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" 'x_player_teammate_7', 'x_player_teammate_8', 'x_player_teammate_9',\n",
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" 'x_player_teammate_10', 'y_player_opponent_Goalkeeper',\n",
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" 'y_player_opponent_8', 'y_player_opponent_1', 'y_player_opponent_2',\n",
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" 'y_player_opponent_3', 'y_player_teammate_1', 'y_player_opponent_4',\n",
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" 'y_player_opponent_5', 'y_player_opponent_6', 'y_player_teammate_2',\n",
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" 'y_player_opponent_9', 'y_player_opponent_10', 'y_player_opponent_11',\n",
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" 'y_player_teammate_3', 'y_player_teammate_4', 'y_player_teammate_5',\n",
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" 'y_player_teammate_6', 'y_player_teammate_7', 'y_player_teammate_8',\n",
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" 'y_player_teammate_9', 'y_player_teammate_10', 'x_player_opponent_7',\n",
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" 'y_player_opponent_7', 'x_player_teammate_Goalkeeper',\n",
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" 'y_player_teammate_Goalkeeper'],\n",
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" dtype='object')"
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]
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},
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"execution_count": 3,
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||
"metadata": {},
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||
"output_type": "execute_result"
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}
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||
],
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"source": [
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"df.columns"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>minute</th>\n",
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" <th>position_name</th>\n",
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" <th>shot_body_part_name</th>\n",
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||
" <th>shot_technique_name</th>\n",
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||
" <th>shot_type_name</th>\n",
|
||
" <th>shot_first_time</th>\n",
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||
" <th>shot_one_on_one</th>\n",
|
||
" <th>shot_aerial_won</th>\n",
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||
" <th>shot_open_goal</th>\n",
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||
" <th>shot_follows_dribble</th>\n",
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||
" <th>...</th>\n",
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||
" <th>y_player_teammate_5</th>\n",
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||
" <th>y_player_teammate_6</th>\n",
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||
" <th>y_player_teammate_7</th>\n",
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||
" <th>y_player_teammate_8</th>\n",
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||
" <th>y_player_teammate_9</th>\n",
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||
" <th>y_player_teammate_10</th>\n",
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||
" <th>x_player_opponent_7</th>\n",
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||
" <th>y_player_opponent_7</th>\n",
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||
" <th>x_player_teammate_Goalkeeper</th>\n",
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||
" <th>y_player_teammate_Goalkeeper</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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||
" <th>0</th>\n",
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||
" <td>2</td>\n",
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||
" <td>Left Center Forward</td>\n",
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||
" <td>Right Foot</td>\n",
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||
" <td>Half Volley</td>\n",
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||
" <td>Open Play</td>\n",
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||
" <td>True</td>\n",
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||
" <td>False</td>\n",
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||
" <td>False</td>\n",
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||
" <td>False</td>\n",
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||
" <td>False</td>\n",
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||
" <td>...</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>26.6</td>\n",
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||
" <td>53.1</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" </tr>\n",
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||
" <tr>\n",
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||
" <th>1</th>\n",
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||
" <td>5</td>\n",
|
||
" <td>Left Back</td>\n",
|
||
" <td>Left Foot</td>\n",
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||
" <td>Volley</td>\n",
|
||
" <td>Open Play</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>20.6</td>\n",
|
||
" <td>32.8</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>23.8</td>\n",
|
||
" <td>31.2</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
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||
" <th>2</th>\n",
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||
" <td>15</td>\n",
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||
" <td>Left Center Forward</td>\n",
|
||
" <td>Left Foot</td>\n",
|
||
" <td>Normal</td>\n",
|
||
" <td>Open Play</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>29.0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>29.6</td>\n",
|
||
" <td>55.3</td>\n",
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||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
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||
" </tr>\n",
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||
" <tr>\n",
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||
" <th>3</th>\n",
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||
" <td>16</td>\n",
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||
" <td>Center Forward</td>\n",
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||
" <td>Head</td>\n",
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||
" <td>Normal</td>\n",
|
||
" <td>Open Play</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>26.7</td>\n",
|
||
" <td>60.4</td>\n",
|
||
" <td>NaN</td>\n",
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||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
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||
" <th>4</th>\n",
|
||
" <td>18</td>\n",
|
||
" <td>Right Center Forward</td>\n",
|
||
" <td>Right Foot</td>\n",
|
||
" <td>Normal</td>\n",
|
||
" <td>Open Play</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>27.9</td>\n",
|
||
" <td>31.4</td>\n",
|
||
" <td>33.4</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>16.9</td>\n",
|
||
" <td>40.1</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>5 rows × 64 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" minute position_name shot_body_part_name shot_technique_name \\\n",
|
||
"0 2 Left Center Forward Right Foot Half Volley \n",
|
||
"1 5 Left Back Left Foot Volley \n",
|
||
"2 15 Left Center Forward Left Foot Normal \n",
|
||
"3 16 Center Forward Head Normal \n",
|
||
"4 18 Right Center Forward Right Foot Normal \n",
|
||
"\n",
|
||
" shot_type_name shot_first_time shot_one_on_one shot_aerial_won \\\n",
|
||
"0 Open Play True False False \n",
|
||
"1 Open Play True False False \n",
|
||
"2 Open Play False False False \n",
|
||
"3 Open Play False False True \n",
|
||
"4 Open Play False False False \n",
|
||
"\n",
|
||
" shot_open_goal shot_follows_dribble ... y_player_teammate_5 \\\n",
|
||
"0 False False ... NaN \n",
|
||
"1 False False ... 20.6 \n",
|
||
"2 False False ... 29.0 \n",
|
||
"3 False False ... NaN \n",
|
||
"4 False False ... 27.9 \n",
|
||
"\n",
|
||
" y_player_teammate_6 y_player_teammate_7 y_player_teammate_8 \\\n",
|
||
"0 NaN NaN NaN \n",
|
||
"1 32.8 NaN NaN \n",
|
||
"2 NaN NaN NaN \n",
|
||
"3 NaN NaN NaN \n",
|
||
"4 31.4 33.4 NaN \n",
|
||
"\n",
|
||
" y_player_teammate_9 y_player_teammate_10 x_player_opponent_7 \\\n",
|
||
"0 NaN NaN 26.6 \n",
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||
"1 NaN NaN 23.8 \n",
|
||
"2 NaN NaN 29.6 \n",
|
||
"3 NaN NaN 26.7 \n",
|
||
"4 NaN NaN 16.9 \n",
|
||
"\n",
|
||
" y_player_opponent_7 x_player_teammate_Goalkeeper \\\n",
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||
"0 53.1 NaN \n",
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||
"1 31.2 NaN \n",
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||
"2 55.3 NaN \n",
|
||
"3 60.4 NaN \n",
|
||
"4 40.1 NaN \n",
|
||
"\n",
|
||
" y_player_teammate_Goalkeeper \n",
|
||
"0 NaN \n",
|
||
"1 NaN \n",
|
||
"2 NaN \n",
|
||
"3 NaN \n",
|
||
"4 NaN \n",
|
||
"\n",
|
||
"[5 rows x 64 columns]"
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||
]
|
||
},
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||
"execution_count": 4,
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||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
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||
"source": [
|
||
"df.head()"
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||
]
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
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||
"source": [
|
||
"# Data preparation"
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||
]
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||
},
|
||
{
|
||
"cell_type": "code",
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||
"execution_count": 43,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
|
||
"# df[['minute', \n",
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"# 'number_of_players_opponents', \n",
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"# 'number_of_players_teammates']] = df[['minute', \n",
|
||
"# 'number_of_players_opponents', \n",
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"# 'number_of_players_teammates']].astype(float)"
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||
]
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||
},
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||
{
|
||
"cell_type": "code",
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||
"execution_count": 4,
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
|
||
"from sklearn.preprocessing import OrdinalEncoder\n",
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"\n",
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||
"enc = OrdinalEncoder()\n",
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"\n",
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"df[['position_name', \n",
|
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" 'shot_technique_name', \n",
|
||
" 'shot_type_name', \n",
|
||
" 'shot_body_part_name']] = enc.fit_transform(df[['position_name', \n",
|
||
" 'shot_technique_name', \n",
|
||
" 'shot_type_name',\n",
|
||
" 'shot_body_part_name']])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"df[['minute', \n",
|
||
" 'position_name', \n",
|
||
" 'shot_technique_name', \n",
|
||
" 'shot_type_name', \n",
|
||
" 'shot_body_part_name']] = df[['minute', \n",
|
||
" 'position_name', \n",
|
||
" 'shot_technique_name', \n",
|
||
" 'shot_type_name', \n",
|
||
" 'shot_body_part_name']].astype(int)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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"\n",
|
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" vertical-align: top;\n",
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"\n",
|
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" .dataframe thead th {\n",
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|
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" <thead>\n",
|
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" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>minute</th>\n",
|
||
" <th>position_name</th>\n",
|
||
" <th>shot_body_part_name</th>\n",
|
||
" <th>shot_technique_name</th>\n",
|
||
" <th>shot_type_name</th>\n",
|
||
" <th>shot_first_time</th>\n",
|
||
" <th>shot_one_on_one</th>\n",
|
||
" <th>shot_aerial_won</th>\n",
|
||
" <th>shot_open_goal</th>\n",
|
||
" <th>shot_follows_dribble</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>y_player_teammate_5</th>\n",
|
||
" <th>y_player_teammate_6</th>\n",
|
||
" <th>y_player_teammate_7</th>\n",
|
||
" <th>y_player_teammate_8</th>\n",
|
||
" <th>y_player_teammate_9</th>\n",
|
||
" <th>y_player_teammate_10</th>\n",
|
||
" <th>x_player_opponent_7</th>\n",
|
||
" <th>y_player_opponent_7</th>\n",
|
||
" <th>x_player_teammate_Goalkeeper</th>\n",
|
||
" <th>y_player_teammate_Goalkeeper</th>\n",
|
||
" </tr>\n",
|
||
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|
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" <tbody>\n",
|
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" <tr>\n",
|
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|
||
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|
||
" <td>3</td>\n",
|
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" <td>4</td>\n",
|
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|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
|
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" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>5</td>\n",
|
||
" <td>18</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>5</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>2</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>48.9</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>5</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>5</td>\n",
|
||
" <td>17</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>38337</th>\n",
|
||
" <td>61</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>47.3</td>\n",
|
||
" <td>42.6</td>\n",
|
||
" <td>54.7</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>21.3</td>\n",
|
||
" <td>50.9</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>38338</th>\n",
|
||
" <td>66</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>47.6</td>\n",
|
||
" <td>39.4</td>\n",
|
||
" <td>43.1</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>19.0</td>\n",
|
||
" <td>45.8</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>38339</th>\n",
|
||
" <td>73</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>6</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>48.9</td>\n",
|
||
" <td>48.1</td>\n",
|
||
" <td>41.1</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>21.7</td>\n",
|
||
" <td>29.6</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>38340</th>\n",
|
||
" <td>75</td>\n",
|
||
" <td>13</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>29.1</td>\n",
|
||
" <td>33.6</td>\n",
|
||
" <td>40.9</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>21.2</td>\n",
|
||
" <td>32.4</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>38341</th>\n",
|
||
" <td>90</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>4</td>\n",
|
||
" <td>3</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>False</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>62.6</td>\n",
|
||
" <td>51.0</td>\n",
|
||
" <td>66.7</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>23.0</td>\n",
|
||
" <td>45.5</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>38342 rows × 64 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" minute position_name shot_body_part_name shot_technique_name \\\n",
|
||
"0 0 18 3 4 \n",
|
||
"1 5 18 1 4 \n",
|
||
"2 5 4 3 2 \n",
|
||
"3 5 10 3 4 \n",
|
||
"4 5 17 1 4 \n",
|
||
"... ... ... ... ... \n",
|
||
"38337 61 3 3 4 \n",
|
||
"38338 66 0 3 4 \n",
|
||
"38339 73 3 1 6 \n",
|
||
"38340 75 13 1 4 \n",
|
||
"38341 90 3 3 4 \n",
|
||
"\n",
|
||
" shot_type_name shot_first_time shot_one_on_one shot_aerial_won \\\n",
|
||
"0 3 False False False \n",
|
||
"1 3 False False False \n",
|
||
"2 3 True False False \n",
|
||
"3 3 False False False \n",
|
||
"4 3 True False False \n",
|
||
"... ... ... ... ... \n",
|
||
"38337 3 True False False \n",
|
||
"38338 3 True False False \n",
|
||
"38339 3 True False False \n",
|
||
"38340 3 False False False \n",
|
||
"38341 3 False False False \n",
|
||
"\n",
|
||
" shot_open_goal shot_follows_dribble ... y_player_teammate_5 \\\n",
|
||
"0 False False ... NaN \n",
|
||
"1 False False ... NaN \n",
|
||
"2 False False ... 48.9 \n",
|
||
"3 False False ... NaN \n",
|
||
"4 False False ... NaN \n",
|
||
"... ... ... ... ... \n",
|
||
"38337 False False ... 47.3 \n",
|
||
"38338 False False ... 47.6 \n",
|
||
"38339 False False ... 48.9 \n",
|
||
"38340 False False ... 29.1 \n",
|
||
"38341 False False ... 62.6 \n",
|
||
"\n",
|
||
" y_player_teammate_6 y_player_teammate_7 y_player_teammate_8 \\\n",
|
||
"0 NaN NaN NaN \n",
|
||
"1 NaN NaN NaN \n",
|
||
"2 NaN NaN NaN \n",
|
||
"3 NaN NaN NaN \n",
|
||
"4 NaN NaN NaN \n",
|
||
"... ... ... ... \n",
|
||
"38337 42.6 54.7 NaN \n",
|
||
"38338 39.4 43.1 NaN \n",
|
||
"38339 48.1 41.1 NaN \n",
|
||
"38340 33.6 40.9 NaN \n",
|
||
"38341 51.0 66.7 NaN \n",
|
||
"\n",
|
||
" y_player_teammate_9 y_player_teammate_10 x_player_opponent_7 \\\n",
|
||
"0 NaN NaN NaN \n",
|
||
"1 NaN NaN NaN \n",
|
||
"2 NaN NaN NaN \n",
|
||
"3 NaN NaN NaN \n",
|
||
"4 NaN NaN NaN \n",
|
||
"... ... ... ... \n",
|
||
"38337 NaN NaN 21.3 \n",
|
||
"38338 NaN NaN 19.0 \n",
|
||
"38339 NaN NaN 21.7 \n",
|
||
"38340 NaN NaN 21.2 \n",
|
||
"38341 NaN NaN 23.0 \n",
|
||
"\n",
|
||
" y_player_opponent_7 x_player_teammate_Goalkeeper \\\n",
|
||
"0 NaN NaN \n",
|
||
"1 NaN NaN \n",
|
||
"2 NaN NaN \n",
|
||
"3 NaN NaN \n",
|
||
"4 NaN NaN \n",
|
||
"... ... ... \n",
|
||
"38337 50.9 NaN \n",
|
||
"38338 45.8 NaN \n",
|
||
"38339 29.6 NaN \n",
|
||
"38340 32.4 NaN \n",
|
||
"38341 45.5 NaN \n",
|
||
"\n",
|
||
" y_player_teammate_Goalkeeper \n",
|
||
"0 NaN \n",
|
||
"1 NaN \n",
|
||
"2 NaN \n",
|
||
"3 NaN \n",
|
||
"4 NaN \n",
|
||
"... ... \n",
|
||
"38337 NaN \n",
|
||
"38338 NaN \n",
|
||
"38339 NaN \n",
|
||
"38340 NaN \n",
|
||
"38341 NaN \n",
|
||
"\n",
|
||
"[38342 rows x 64 columns]"
|
||
]
|
||
},
|
||
"execution_count": 46,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"['labelEncoder.joblib']"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"dump(enc,'labelEncoder.joblib')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"enc2 = load('labelEncoder.joblib')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 49,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# df[['position_name', \n",
|
||
"# 'shot_technique_name', \n",
|
||
"# 'shot_type_name', \n",
|
||
"# 'shot_body_part_name']] = enc2.inverse_transform(df[['position_name', \n",
|
||
"# 'shot_technique_name', \n",
|
||
"# 'shot_type_name',\n",
|
||
"# 'shot_body_part_name']])\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 50,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# df[['position_name', \n",
|
||
"# 'shot_technique_name', \n",
|
||
"# 'shot_type_name', \n",
|
||
"# 'shot_body_part_name']] = enc2.transform(df[['position_name', \n",
|
||
"# 'shot_technique_name', \n",
|
||
"# 'shot_type_name', \n",
|
||
"# 'shot_body_part_name']])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 51,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# enc.inverse_transform(df[['position_name', \n",
|
||
"# 'shot_technique_name', \n",
|
||
"# 'shot_type_name',\n",
|
||
"# 'shot_body_part_name']])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 52,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# ############### NEW ################\n",
|
||
"# from sklearn.preprocessing import LabelEncoder\n",
|
||
"\n",
|
||
"# le_posiotion_name = LabelEncoder()\n",
|
||
"# le_shot_technique_name = LabelEncoder()\n",
|
||
"# le_shot_type_name = LabelEncoder()\n",
|
||
"# le_shot_body_part_name = LabelEncoder()\n",
|
||
"\n",
|
||
"# df['position_name'] = le_posiotion_name.fit_transform(df['position_name'])\n",
|
||
"# df['shot_technique_name'] = le_shot_technique_name.fit_transform(df['shot_technique_name'])\n",
|
||
"# df['shot_type_name'] = le_shot_type_name.fit_transform(df['shot_type_name'])\n",
|
||
"# df['shot_body_part_name'] = le_shot_body_part_name.fit_transform(df['shot_body_part_name'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Change the type of categorical features to 'category' \n",
|
||
"df[['minute',\n",
|
||
" 'position_name', \n",
|
||
" 'shot_technique_name', \n",
|
||
" 'shot_type_name', \n",
|
||
" 'number_of_players_opponents', \n",
|
||
" 'number_of_players_teammates', \n",
|
||
" 'shot_body_part_name']] = df[['minute',\n",
|
||
" 'position_name', \n",
|
||
" 'shot_technique_name', \n",
|
||
" 'shot_type_name', \n",
|
||
" 'number_of_players_opponents', \n",
|
||
" 'number_of_players_teammates', \n",
|
||
" 'shot_body_part_name']].astype('category')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Splitting the dataset into features (X) and the target variable (y)\n",
|
||
"y = pd.DataFrame(df['is_goal'])\n",
|
||
"X = df.drop(['is_goal'], axis=1)\n",
|
||
"\n",
|
||
"# Splitting the data into a training set and a test set\n",
|
||
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1)\n",
|
||
"\n",
|
||
"# Create cross-validation \n",
|
||
"cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=1)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Shots attempted in the training set: 58970\n",
|
||
"Goals scored in the training set: 7286\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"count_class_0, count_class_1 = y_train.value_counts()\n",
|
||
"\n",
|
||
"# Display the count of shots attempted in the training set\n",
|
||
"print('Shots attempted in the training set:', count_class_0)\n",
|
||
"\n",
|
||
"# Display the count of successful goals in the training set\n",
|
||
"print('Goals scored in the training set:', count_class_1)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" Class imbalance in training data: 8.094\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Class imbalance in training data\n",
|
||
"scale_pos_weight = count_class_0 / count_class_1\n",
|
||
"print(f' Class imbalance in training data: {scale_pos_weight:.3f}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Training XGBoost model "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Define the xgboost model\n",
|
||
"xgb_model = xgboost.XGBClassifier(enable_categorical=True, tree_method='hist', objective='binary:logistic')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Defining the hyper-parameter grid for XG Boost\n",
|
||
"param_grid_xgb = {'learning_rate': [0.01, 0.001, 0.0001],\n",
|
||
" 'max_depth': [3, 5, 7, 8, 9],\n",
|
||
" 'n_estimators': [100, 150, 200, 250, 300],\n",
|
||
" 'scale_pos_weight': [1, scale_pos_weight]}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Starting the timer\n",
|
||
"start_time = time.time()\n",
|
||
"\n",
|
||
"# Perform grid search with cross-validation\n",
|
||
"grid_xg = GridSearchCV(xgb_model, param_grid=param_grid_xgb, cv=cv, scoring='neg_mean_squared_error', n_jobs=-1)\n",
|
||
"\n",
|
||
"# Fit the best model on the entire training set\n",
|
||
"grid_xg.fit(X_train, y_train)\n",
|
||
"\n",
|
||
"# Take the best parameters for xgboost model\n",
|
||
"best_xgb_model = grid_xg.best_estimator_\n",
|
||
"\n",
|
||
"# Stopping the timer\n",
|
||
"stop_time = time.time()\n",
|
||
"\n",
|
||
"# Training Time\n",
|
||
"xgb_training_time = stop_time - start_time"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Best parameters: {'learning_rate': 0.01, 'max_depth': 5, 'n_estimators': 250, 'scale_pos_weight': 1}\n",
|
||
"Model Training Time: 1550.563 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Print the best parameters and training time\n",
|
||
"print(\"Best parameters: \", grid_xg.best_params_)\n",
|
||
"print (f\"Model Training Time: {xgb_training_time:.3f} seconds\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Model evaluation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Training set"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Evaluate the model on training set\n",
|
||
"y_pred_train = best_xgb_model.predict(X_train)\n",
|
||
"\n",
|
||
"# Confusion Matrix for Training Data\n",
|
||
"cm_train_xg = confusion_matrix(y_train, y_pred_train)\n",
|
||
"ax = sns.heatmap(cm_train_xg, annot=True, cmap='BuPu', fmt='g', linewidth=1.5)\n",
|
||
"ax.set_xlabel('Predicted')\n",
|
||
"ax.set_ylabel('Actual')\n",
|
||
"ax.set_title('Confusion Matrix - Train Set')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Test set"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Evaluate the model on test set\n",
|
||
"y_pred_test = best_xgb_model.predict(X_test)\n",
|
||
"\n",
|
||
"# Confusion Matrix for Testig Data\n",
|
||
"cm_test_xgb = confusion_matrix(y_test, y_pred_test)\n",
|
||
"ax = sns.heatmap(cm_test_xgb, annot=True, cmap='Blues', fmt='g', linewidth=1.5)\n",
|
||
"ax.set_xlabel('Predicted')\n",
|
||
"ax.set_ylabel('Actual')\n",
|
||
"ax.set_title('Confusion Matrix - Test Set')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"The test dataset contains 16565 shots, with 1891 of them being goals.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Number of goals in test set\n",
|
||
"print(f'The test dataset contains {len(y_test)} shots, with {y_test.sum()[\"is_goal\"]} of them being goals.')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Feature importance"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Plot feature importance with Gain\n",
|
||
"xgboost.plot_importance(best_xgb_model, importance_type='gain', xlabel='Gain', max_num_features=20)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Plot feature importance with Weight\n",
|
||
"xgboost.plot_importance(best_xgb_model, importance_type='weight', xlabel='Weight', max_num_features=30)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Summary"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Calculating MAE, RMSE and R2 for training and test sets \n",
|
||
"mae_train = mean_absolute_error(y_train, y_pred_train)\n",
|
||
"rmse_train = mean_squared_error(y_train, y_pred_train, squared=False)\n",
|
||
"r2_train = r2_score(y_train, y_pred_train)\n",
|
||
"\n",
|
||
"mae_test = mean_absolute_error(y_test, y_pred_test)\n",
|
||
"rmse_test = mean_squared_error(y_test, y_pred_test, squared=False)\n",
|
||
"r2_test = r2_score(y_test, y_pred_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<style type=\"text/css\">\n",
|
||
"#T_295e5_row0_col0, #T_295e5_row0_col1, #T_295e5_row0_col2, #T_295e5_row0_col3, #T_295e5_row0_col4, #T_295e5_row0_col5, #T_295e5_row0_col6 {\n",
|
||
" font-weight: bold;\n",
|
||
" border: 2.0px solid grey;\n",
|
||
" color: white;\n",
|
||
"}\n",
|
||
"</style>\n",
|
||
"<table id=\"T_295e5\">\n",
|
||
" <thead>\n",
|
||
" <tr>\n",
|
||
" <th class=\"blank level0\" > </th>\n",
|
||
" <th id=\"T_295e5_level0_col0\" class=\"col_heading level0 col0\" >Training MAE</th>\n",
|
||
" <th id=\"T_295e5_level0_col1\" class=\"col_heading level0 col1\" >Training RMSE</th>\n",
|
||
" <th id=\"T_295e5_level0_col2\" class=\"col_heading level0 col2\" >Training R2</th>\n",
|
||
" <th id=\"T_295e5_level0_col3\" class=\"col_heading level0 col3\" >Testing MAE</th>\n",
|
||
" <th id=\"T_295e5_level0_col4\" class=\"col_heading level0 col4\" >Testing RMSE</th>\n",
|
||
" <th id=\"T_295e5_level0_col5\" class=\"col_heading level0 col5\" >Testing R2</th>\n",
|
||
" <th id=\"T_295e5_level0_col6\" class=\"col_heading level0 col6\" >Training Time (mins)</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th class=\"index_name level0\" >Model Name</th>\n",
|
||
" <th class=\"blank col0\" > </th>\n",
|
||
" <th class=\"blank col1\" > </th>\n",
|
||
" <th class=\"blank col2\" > </th>\n",
|
||
" <th class=\"blank col3\" > </th>\n",
|
||
" <th class=\"blank col4\" > </th>\n",
|
||
" <th class=\"blank col5\" > </th>\n",
|
||
" <th class=\"blank col6\" > </th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th id=\"T_295e5_level0_row0\" class=\"row_heading level0 row0\" >XG Boost</th>\n",
|
||
" <td id=\"T_295e5_row0_col0\" class=\"data row0 col0\" >0.09622</td>\n",
|
||
" <td id=\"T_295e5_row0_col1\" class=\"data row0 col1\" >0.31019</td>\n",
|
||
" <td id=\"T_295e5_row0_col2\" class=\"data row0 col2\" >0.01693</td>\n",
|
||
" <td id=\"T_295e5_row0_col3\" class=\"data row0 col3\" >0.09949</td>\n",
|
||
" <td id=\"T_295e5_row0_col4\" class=\"data row0 col4\" >0.31542</td>\n",
|
||
" <td id=\"T_295e5_row0_col5\" class=\"data row0 col5\" >0.01620</td>\n",
|
||
" <td id=\"T_295e5_row0_col6\" class=\"data row0 col6\" >25.84271</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n"
|
||
],
|
||
"text/plain": [
|
||
"<pandas.io.formats.style.Styler at 0x156feb3d0>"
|
||
]
|
||
},
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Creating of dataframe of summary results\n",
|
||
"summary_df = pd.DataFrame({'Model Name':['XG Boost'],\n",
|
||
" 'Training MAE': mae_train, \n",
|
||
" 'Training RMSE': rmse_train,\n",
|
||
" 'Training R2':r2_train,\n",
|
||
" 'Testing MAE': mae_test, \n",
|
||
" 'Testing RMSE': rmse_test,\n",
|
||
" 'Testing R2':r2_test,\n",
|
||
" 'Training Time (mins)': xgb_training_time/60})\n",
|
||
"summary_df.set_index('Model Name', inplace=True)\n",
|
||
"\n",
|
||
"# Displaying summary of results\n",
|
||
"summary_df.style.format(precision =5).set_properties(**{'font-weight': 'bold',\n",
|
||
" 'border': '2.0px solid grey','color': 'white'})"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Keeping the xgboost model"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'objective': 'binary:logistic',\n",
|
||
" 'base_score': None,\n",
|
||
" 'booster': None,\n",
|
||
" 'callbacks': None,\n",
|
||
" 'colsample_bylevel': None,\n",
|
||
" 'colsample_bynode': None,\n",
|
||
" 'colsample_bytree': None,\n",
|
||
" 'device': None,\n",
|
||
" 'early_stopping_rounds': None,\n",
|
||
" 'enable_categorical': True,\n",
|
||
" 'eval_metric': None,\n",
|
||
" 'feature_types': None,\n",
|
||
" 'gamma': None,\n",
|
||
" 'grow_policy': None,\n",
|
||
" 'importance_type': None,\n",
|
||
" 'interaction_constraints': None,\n",
|
||
" 'learning_rate': 0.01,\n",
|
||
" 'max_bin': None,\n",
|
||
" 'max_cat_threshold': None,\n",
|
||
" 'max_cat_to_onehot': None,\n",
|
||
" 'max_delta_step': None,\n",
|
||
" 'max_depth': 5,\n",
|
||
" 'max_leaves': None,\n",
|
||
" 'min_child_weight': None,\n",
|
||
" 'missing': nan,\n",
|
||
" 'monotone_constraints': None,\n",
|
||
" 'multi_strategy': None,\n",
|
||
" 'n_estimators': 250,\n",
|
||
" 'n_jobs': None,\n",
|
||
" 'num_parallel_tree': None,\n",
|
||
" 'random_state': None,\n",
|
||
" 'reg_alpha': None,\n",
|
||
" 'reg_lambda': None,\n",
|
||
" 'sampling_method': None,\n",
|
||
" 'scale_pos_weight': 1,\n",
|
||
" 'subsample': None,\n",
|
||
" 'tree_method': 'hist',\n",
|
||
" 'validate_parameters': None,\n",
|
||
" 'verbosity': None}"
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Save the model\n",
|
||
"best_xgb_model.save_model('xgboost.json')\n",
|
||
"\n",
|
||
"best_xgb_model.get_params()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 69,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Save the model\n",
|
||
"# dump(best_xgb_model, 'xgboost.joblib') \n",
|
||
"\n",
|
||
"# # Load the model\n",
|
||
"# model = load('xgboost.joblib')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([[0.9005616 , 0.09943844],\n",
|
||
" [0.938443 , 0.06155698],\n",
|
||
" [0.96434194, 0.03565805],\n",
|
||
" ...,\n",
|
||
" [0.8334278 , 0.1665722 ],\n",
|
||
" [0.8697108 , 0.13028917],\n",
|
||
" [0.96131223, 0.03868778]], dtype=float32)"
|
||
]
|
||
},
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"best_xgb_model.predict_proba(X)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"new_xgb_model = xgboost.XGBClassifier()\n",
|
||
"new_xgb_model.load_model('xgboost.json')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([[0.9005616 , 0.09943844],\n",
|
||
" [0.938443 , 0.06155698],\n",
|
||
" [0.96434194, 0.03565805],\n",
|
||
" ...,\n",
|
||
" [0.8334278 , 0.1665722 ],\n",
|
||
" [0.8697108 , 0.13028917],\n",
|
||
" [0.96131223, 0.03868778]], dtype=float32)"
|
||
]
|
||
},
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"new_xgb_model.predict_proba(X)"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.11.6"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|