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Kaggle Competition - Analysis and prediction of PUBG players' finishing placement based on their final stats

Home Page: https://www.kaggle.com/c/pubg-finish-placement-prediction/data

Python 100.00%
kaggle-competition pubg regression-models regression-analysis feature-engineering feature-selection auc f1-score linear-regression ridge-regression lasso-regression random-forest-regressor gradient-boosting-regressor lgbm pandas group-by xgboost python kernel

kaggle-pubg-finish-placement-prediction's Introduction

Kaggle Competition - PUBG Finish Placement Prediction

  • This project is taken up from Kaggle, an online community of data scientists and machine learners (link to competition)
  • The goal of the project is to predict PUBG player’s win place percentage based on the player’s statistics.
  • Millions of players data is used for building a regression model.
  • Players data within a group in a match is combined to reduce the dataset size.
  • Some insightful derived features are added to improve the predictions.
  • The best model using Light Gradient Method achieved a Kaggle leaderboard score of 0.0214 on test data.
  • For more information about data analysis and various experiment results, kindly look into doc.pdf file.
  • Final code for prediction is given in main.py file.

Model training

model-1

Model testing

model-1

Different approaches

model-1

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