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