Building a Better Decision Tree by Delaying the Split Decision
Kyle A. Caudle, Larry D. Pyeatt, Anthony Morast, Christer Karlsson, Randy C. Hoover · 2019
Binary decision trees are non-linear prediction models dating back to Breiman's work in the 1980's. The standard algorithm for building a decision tree is a greedy approach whereby all variables and levels of the variable are cycled through until the partition is found that minimizes the impurity of the partition. Our approach delays the split decision one or more steps. We have found that delaying the split decision just one level often provides a tree with better statistical properties and better predictive capability.