All glossary terms
modelsintermediate
Gradient Boosting
An ensemble method that sequentially builds trees, each correcting errors of previous trees.
In more detail
Gradient boosting trains trees sequentially, where each tree fits residuals of previous trees. Powerful for both classification and regression. Popular implementations: XGBoost, LightGBM, CatBoost. Often wins Kaggle competitions.
Examples
- XGBoost for tabular data
- LightGBM for large datasets
- CatBoost for categorical features
Related terms
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