Boosting tree 以决策树为基学习器的boosting称为提升树 (boosting tree),决策树可以是分类树和回归树,一般采用二叉树。 对于分类问题,直接将基学习器设置成分类树即可。 Boosting 是一种将弱分类器转化为强分类器的方法统称,而adaboost是其中的一种,采用了exponential loss function(其实就是用指数的权重),根据不同的loss function还可.
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