<ul><li>Gradient boosting algorithms have become popular in actuarial applications for their superior predictive performance.</li><li>A comprehensive study compares various gradient boosting algorithms, including GBM, XGBoost, DART, LightGBM, CatBoost, EGBM, PGBM, XGBoostLSS, cyclic GBM, and NGBoost.</li><li>The study assesses their performance on claim frequency and severity prediction using different datasets.</li><li>LightGBM and XGBoostLSS are found to be computationally efficient, while EGBM achieves competitive predictive performance with interpretability.</li></ul>

From Point to probabilistic gradient boosting for claim frequency and severity prediction

Discover more