openml==0.10.2,sklearn==0.23.1 0 Gradient Boosting for classification. GB builds an additive model in a forward stage-wise fashion; it allows for the optimization of arbitrary differentiable loss functions. In each stage ``n_classes_`` regression trees are fit on the negative gradient of the binomial or multinomial deviance loss function. Binary classification is a special case where only a single regression tree is induced. 0 sklearn==0.23.1 numpy>=1.6.1 scipy>=0.9 18689 0 2 sklearn.ensemble._gb.GradientBoostingClassifier public 2020-01-29T21:07:55Z sklearn.ensemble._gb.GradientBoostingClassifier