Difference between regression tree and model tree

Question

I need some help in understanding the difference between regression trees and linear model tree.

Regards

Shahzad

Answer 1

A linear model tree is a decision tree with a linear functional model in each leaf, whereas in classical regression tree (e.g., CART) it is the sample mean of the response variable for statistical units in each leaf (hence, a constant) that is being considered. Linear model trees can be seen as a a form of locally weighted regression, while regression tree are piecewise-constant regression.

For more information on linear model trees, you can consult

Torgo, L. Functional models for regression tree leaves. In Proceedings of the 14th International Conference on Machine Learning, pp. 385–393. Morgan Kaufmann, 1997.