En form av ensembleinlärningsmetod som kombinerar svaga inlärningsmodeller för att skapa starka, vilket minskar inlärningsfel och bias i inlärningsmodellerna. Det finns olika typer av boosting, t.ex. gradient boosting, XGBoost och Adaboost.
A form of ensemble learning methods which combines weak learners to create strong ones, which reduces training errors and bias in the training models. There are different types of boosting such as gradient boosting, XGBoost, and Adaboost.
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Machine Learning Boosting Algorithms — Boosting, Machine Learning — Machine Learning Boosting — Machine Learning Boostings — Ensemble Machine Learning Boosting — Adaptive Boosting Algorithms — Adaptive Boosting Algorithm — Algorithm, Adaptive Boosting — Boosting Algorithm, Adaptive — Adaboost — Adaboosts — Iterative Model Building — Gradient Boosting Algorithms — Algorithm, Gradient Boosting — Boosting Algorithm, Gradient — Gradient Boosting Algorithm — Extreme Gradient Boost — Extreme Gradient Boosts — Gradient Boost, Extreme — XGBoost — XGBoosts — Light Gradient Boosting Machine — LightGBM — Categorical Boosting — Boosting, Categorical — Categorical Boostings — Categorical Boosting Algorithms — Algorithm, Categorical Boosting — Boosting Algorithm, Categorical — Categorical Boosting Algorithm — CatBoost