Difference Between Boosting Trees: Updates to Classics With CatBoost, XGBoost and LightGBM

This publication discusses the differences between popular boosting tree algorithms such as CatBoost, XGBoost, and LightGBM. It covers the historical development of boosting techniques, starting with AdaBoost, and moving on to Gradient Boosting Machines (GBM), XGBoost, LightGBM, and CatBoost. Each algorithm has unique features and strengths, with CatBoost excelling in handling categorical features, XGBoost offering high performance and regularization, and LightGBM focusing on speed and efficiency. The choice of the algorithm depends on the problem and dataset, and it's recommended …

adaboost ai ai technology ai-top-story algorithm algorithms boosting catboost categorical data science dataset development difference efficiency features gradient gradient-boosting lightgbm machine learning & ai machines ml ml-algorithm moving performance popular publication regularization speed tree trees updates xgboost