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...widely used algorithm AdaBoost (Adaptive Boosting) with Schapire in 1997. Boosting algorithms work by iteratively adjusting the weights of data points based o ==Boosting Algorithm==

...oduce a more accurate and robust prediction. The main idea behind gradient boosting is to sequentially add weak learners (typically decision trees) to the ense In gradient boosting, the primary goal is to minimize a [[loss function]]. The loss function qua

| '''[[AGC]]''' || || [[Adaptive Gradient Clipping]] | '''[[CatBoost]]''' || || [[Categorical Boosting]]