# 目录 [−]

## 决策树和随机森林

golearn支持两种决策树算法。ID3和RandomTree。

• ID3: 以信息增益为准则选择信息增益最大的属性。

ID3 is a decision tree induction algorithm which splits on the Attribute which gives the greatest Information Gain (entropy gradient). It performs well on categorical data. Numeric datasets will need to be discretised before using ID3

• RandomTree: 与ID3类似，但是选择的属性的时候随机选择。

Random Trees are structurally identical to those generated by ID3, but the split Attribute is chosen randomly. Golearn's implementation allows you to choose up to k nodes for consideration at each split.