Question

What are the methods based on which nodes are split in a decision tree? How do they differ?

Answer 1

Decision trees are trained by passing data down from a root node to leaves. The data is repeatedly split according to predictor variables so that child nodes are more “pure” (i.e., homogeneous) in terms of the outcome variable. ... The colored dots indicate classes which will eventually be separated by the decision tree.