Also known as: GBT Β· decision
Gradient Boosted Decision Trees (GBT) are decision forest models trained through gradient boosting. They build an ensemble of decision trees sequentially, with each tree correcting errors made by earlier trees.
A type of decision forest in which: - Training relies on gradient boosting. - The weak model is a decision tree. See Gradient Boosted Decision Trees in the Decision Forests course for more information.