GBDT

什么是GBDT

一下是wiki有关GBDT的介绍：

Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do, and it generalizes them by allowing optimization of an arbitrary differentiable loss function.

题外话，wiki还是满靠谱的。

GB（Gradient Boosting）既用于回归问题，又用于分类问题，我有点惊到。DT（Decision Trees）