to comprehensively assess predictive performance. For frequency prediction, extreme gradient boosting (XGBoost …) demonstrates the lowest MAE, indicating higher accuracy compared to gradient boosting machines (GBMs) and a generalized linear … magnitudes compared to gradient boosting machines (GBMs) and a generalized linear model (Poisson). Conversely, the generalized …

boosting models that are found to perform well individually. Empirical tests have been carried out on an openly available …

been introduced. In this article, we propose a novel model-based gradient boosting approach for Dirichlet regression models …

approach including boosting, bagging, and voting techniques was used for obesity risk prediction based on lifestyle dataset …. Specifically, XGBoost, Gradient Boosting, and CatBoost models are used for boosting, Bagged Decision Tree, Random Forest, and Extra …

This study applies Gradient Boosting Machines (GBMs) and principal component regression (PCR) to forecast the closing …