351 lines
15 KiB
Plaintext
351 lines
15 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "a3a7634f",
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"metadata": {},
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"source": [
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"# Machine Learning project in SoSe 2025 at HTW Saar\n",
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"## Idea\n",
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"The goal of this project is getting the genre(s) of a game trough its given metadata\n",
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"\n",
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"## Dataset\n",
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"For our project we use a Steam DataSet from kaggle. You can find it under the following URL: [Kaggle.com](https://www.kaggle.com/datasets/artermiloff/steam-games-dataset/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": 16,
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"id": "3116b75f",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" appid name release_date required_age price \\\n",
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"0 730 Counter-Strike 2 2012-08-21 0 0.00 \n",
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"1 578080 PUBG: BATTLEGROUNDS 2017-12-21 0 0.00 \n",
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"2 570 Dota 2 2013-07-09 0 0.00 \n",
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"3 271590 Grand Theft Auto V Legacy 2015-04-13 17 0.00 \n",
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"4 359550 Tom Clancy's Rainbow Six® Siege 2015-12-01 17 3.99 \n",
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"\n",
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" dlc_count detailed_description \\\n",
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"0 1 For over two decades, Counter-Strike has offer... \n",
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"1 0 LAND, LOOT, SURVIVE! Play PUBG: BATTLEGROUNDS ... \n",
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"2 2 The most-played game on Steam. Every day, mill... \n",
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"3 0 When a young street hustler, a retired bank ro... \n",
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"4 9 Edition Comparison Ultimate Edition The Tom Cl... \n",
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"\n",
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" about_the_game \\\n",
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"0 For over two decades, Counter-Strike has offer... \n",
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"1 LAND, LOOT, SURVIVE! Play PUBG: BATTLEGROUNDS ... \n",
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"2 The most-played game on Steam. Every day, mill... \n",
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"3 When a young street hustler, a retired bank ro... \n",
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"4 “One of the best first-person shooters ever ma... \n",
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"\n",
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" short_description \\\n",
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"0 For over two decades, Counter-Strike has offer... \n",
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"1 Play PUBG: BATTLEGROUNDS for free. Land on str... \n",
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"2 Every day, millions of players worldwide enter... \n",
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"3 Grand Theft Auto V for PC offers players the o... \n",
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"4 Tom Clancy's Rainbow Six® Siege is an elite, t... \n",
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"\n",
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" reviews ... \\\n",
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"0 NaN ... \n",
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"1 NaN ... \n",
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"2 “A modern multiplayer masterpiece.” 9.5/10 – D... ... \n",
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"3 NaN ... \n",
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"4 NaN ... \n",
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"\n",
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" average_playtime_2weeks median_playtime_forever median_playtime_2weeks \\\n",
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"0 879 5174 350 \n",
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"1 0 0 0 \n",
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"2 1536 898 892 \n",
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"3 771 7101 74 \n",
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"4 682 2434 306 \n",
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"\n",
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" discount peak_ccu tags \\\n",
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"0 0 1212356 {'FPS': 90857, 'Shooter': 65397, 'Multiplayer'... \n",
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"1 0 616738 {'Survival': 14838, 'Shooter': 12727, 'Battle ... \n",
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"2 0 555977 {'Free to Play': 59933, 'MOBA': 20158, 'Multip... \n",
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"3 0 117698 {'Open World': 32644, 'Action': 23539, 'Multip... \n",
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"4 80 89916 {'FPS': 9831, 'PvP': 9162, 'e-sports': 9072, '... \n",
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"\n",
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" pct_pos_total num_reviews_total pct_pos_recent num_reviews_recent \n",
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"0 86 8632939 82 96473 \n",
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"1 59 2513842 68 16720 \n",
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"2 81 2452595 80 29366 \n",
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"3 87 1803832 92 17517 \n",
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"4 84 1168020 76 12608 \n",
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"\n",
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"[5 rows x 47 columns]\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"\n",
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"# load data\n",
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"# appid,name,release_date,required_age,price,dlc_count,detailed_description,about_the_game,short_description,reviews,header_image,website,support_url,support_email,windows,mac,linux,metacritic_score,metacritic_url,achievements,recommendations,notes,supported_languages,full_audio_languages,packages,developers,publishers,categories,genres,screenshots,movies,user_score,score_rank,positive,negative,estimated_owners,average_playtime_forever,average_playtime_2weeks,median_playtime_forever,median_playtime_2weeks,discount,peak_ccu,tags,pct_pos_total,num_reviews_total,pct_pos_recent,num_reviews_recent\n",
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"dataset = pd.read_csv(\"./games_march2025_cleaned.csv\",sep=\",\")\n",
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"print(dataset.head())"
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]
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},
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{
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"cell_type": "markdown",
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"id": "cba9750a",
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"metadata": {},
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"source": [
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"## Preparation of the Training-Set\n",
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"### Removing Uniques\n",
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"We remove the following features from the Training-Set as they can uniquely identify a datapoint:\n",
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"- AppId\n",
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"- Name of the Game\n",
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"- Realease Date\n",
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"- Header Image\n",
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"- Website\n",
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"- Support URL\n",
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"- Support Email\n",
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"- MetaCritic URL\n",
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"- Developer\n",
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"- Publisher\n",
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"- Screenshots\n",
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"- Movies\n",
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"- Estimated Owners"
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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": 17,
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"id": "06dedcdf",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" required_age price dlc_count \\\n",
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"0 0 0.00 1 \n",
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"1 0 0.00 0 \n",
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"2 0 0.00 2 \n",
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"3 17 0.00 0 \n",
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"4 17 3.99 9 \n",
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"\n",
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" detailed_description \\\n",
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"0 For over two decades, Counter-Strike has offer... \n",
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"1 LAND, LOOT, SURVIVE! Play PUBG: BATTLEGROUNDS ... \n",
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"2 The most-played game on Steam. Every day, mill... \n",
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"3 When a young street hustler, a retired bank ro... \n",
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"4 Edition Comparison Ultimate Edition The Tom Cl... \n",
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"\n",
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" about_the_game \\\n",
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"0 For over two decades, Counter-Strike has offer... \n",
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"1 LAND, LOOT, SURVIVE! Play PUBG: BATTLEGROUNDS ... \n",
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"2 The most-played game on Steam. Every day, mill... \n",
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"3 When a young street hustler, a retired bank ro... \n",
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"4 “One of the best first-person shooters ever ma... \n",
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"\n",
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" short_description \\\n",
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"0 For over two decades, Counter-Strike has offer... \n",
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"1 Play PUBG: BATTLEGROUNDS for free. Land on str... \n",
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"2 Every day, millions of players worldwide enter... \n",
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"3 Grand Theft Auto V for PC offers players the o... \n",
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"4 Tom Clancy's Rainbow Six® Siege is an elite, t... \n",
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"\n",
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" reviews windows mac linux \\\n",
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"0 NaN True False True \n",
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"1 NaN True False False \n",
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"2 “A modern multiplayer masterpiece.” 9.5/10 – D... True True True \n",
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"3 NaN True False False \n",
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"4 NaN True False False \n",
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"\n",
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" ... average_playtime_2weeks median_playtime_forever \\\n",
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"0 ... 879 5174 \n",
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"1 ... 0 0 \n",
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"2 ... 1536 898 \n",
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"3 ... 771 7101 \n",
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"4 ... 682 2434 \n",
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"\n",
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" median_playtime_2weeks discount peak_ccu \\\n",
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"0 350 0 1212356 \n",
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"1 0 0 616738 \n",
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"2 892 0 555977 \n",
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"3 74 0 117698 \n",
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"4 306 80 89916 \n",
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"\n",
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" tags pct_pos_total \\\n",
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"0 {'FPS': 90857, 'Shooter': 65397, 'Multiplayer'... 86 \n",
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"1 {'Survival': 14838, 'Shooter': 12727, 'Battle ... 59 \n",
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"2 {'Free to Play': 59933, 'MOBA': 20158, 'Multip... 81 \n",
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"3 {'Open World': 32644, 'Action': 23539, 'Multip... 87 \n",
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"4 {'FPS': 9831, 'PvP': 9162, 'e-sports': 9072, '... 84 \n",
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"\n",
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" num_reviews_total pct_pos_recent num_reviews_recent \n",
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"0 8632939 82 96473 \n",
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"1 2513842 68 16720 \n",
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"2 2452595 80 29366 \n",
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"3 1803832 92 17517 \n",
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"4 1168020 76 12608 \n",
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"\n",
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"[5 rows x 34 columns]\n"
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]
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}
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],
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"source": [
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"# appid,name,release_date,required_age,price,dlc_count,detailed_description,about_the_game,short_description,reviews,header_image,website,support_url,support_email,windows,mac,linux,metacritic_score,metacritic_url,achievements,recommendations,notes,supported_languages,full_audio_languages,packages,developers,publishers,categories,genres,screenshots,movies,user_score,score_rank,positive,negative,estimated_owners,average_playtime_forever,average_playtime_2weeks,median_playtime_forever,median_playtime_2weeks,discount,peak_ccu,tags,pct_pos_total,num_reviews_total,pct_pos_recent,num_reviews_recent\n",
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"dataset.drop(['appid', 'name', 'release_date', 'header_image', 'website', 'support_url', 'support_email', 'metacritic_url', 'developers', 'publishers', 'screenshots', 'movies', 'estimated_owners'], axis=1, inplace=True)\n",
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"print(dataset.head())"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f5436c87",
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"metadata": {},
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"source": [
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"### Structurize Text\n",
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"**TODO: check if makes sense**\n",
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"The dataset holds a lot of unstructured data, we use Term Frequency-Inverse Document Frequency to structurize most Text-Features.\n",
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"It is important to use an new Instance for each feature so they don't overlap with each other. \n",
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"\n",
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"### Standardize Values\n",
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"We standardize only the text features to remove the stop words. The dataset allready provides standardized numerical features."
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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": null,
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"id": "4e8b407c",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[1. 1. 1. 1.]]\n"
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]
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}
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],
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"source": [
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"from sklearn.compose import make_column_transformer\n",
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"from sklearn.feature_extraction.text import TfidfVectorizer\n",
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"# appid,name,release_date,required_age,price,dlc_count,detailed_description,about_the_game,short_description,reviews,header_image,website,support_url,support_email,windows,mac,linux,metacritic_score,metacritic_url,achievements,recommendations,notes,supported_languages,full_audio_languages,packages,developers,publishers,categories,genres,screenshots,movies,user_score,score_rank,positive,negative,estimated_owners,average_playtime_forever,average_playtime_2weeks,median_playtime_forever,median_playtime_2weeks,discount,peak_ccu,tags,pct_pos_total,num_reviews_total,pct_pos_recent,num_reviews_recent\n",
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"column_transformer = make_column_transformer(\n",
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" (TfidfVectorizer(stop_words='english'), ['detailed_description']),\n",
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" (TfidfVectorizer(stop_words='english'), ['about_the_game']),\n",
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" (TfidfVectorizer(stop_words='english'), ['short_description']),\n",
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" (TfidfVectorizer(stop_words='english'), ['reviews']),\n",
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")\n",
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"\n",
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"dataset2 = column_transformer.fit_transform(dataset)\n",
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"print(dataset2)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ad84e777",
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"metadata": {},
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"source": [
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"\n",
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"### Removing Bundles\n",
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"**(TODO: decide whether yes or no), not as important as i thought**\n",
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"As bundles don't have clear genre(s) defined (e.g. publisher bundles )"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6a2a3d4f",
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"metadata": {},
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"source": [
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"### Setting missing values\n",
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"**TODO: Removing or Setting values that are not set or NaN in the DataSet**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "091d7e13",
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"metadata": {},
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"source": [
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"# Data Split\n",
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"**TODO splitting the Data into Train, test and validation data**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "12b5283d",
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"metadata": {},
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"source": [
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"# Model Selection\n",
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"**TODO Deciding which model to use for this task**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b7795aa1",
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"metadata": {},
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"source": [
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"### Training\n",
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"**TODO Train the Selected Model with the training data**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0faa9856",
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"metadata": {},
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"source": [
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"# Evaluation\n",
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"**TODO Test the Model with the test data**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2aeb6fc2",
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"metadata": {},
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"source": [
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"# Optimization\n",
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"**TODO optimize the model based on the test results**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "79b20645",
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"metadata": {},
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"source": [
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"# Validation\n",
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"**TODO Predict actual values**"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3b709fb7",
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"metadata": {},
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"source": [
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"# Conclusion and outlook\n",
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"**TODO Write a conclusion and outlook what can be done and where the issues were.**"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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