Tree Structured Interpretable Regression
Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, PMLR R0:331-341, 1995.
We describe a new method of regression closely related to the regression ideas CART. which has the following potential advantages over traditional methods: the method can naturally be applied to very large datasets in which only a small proportion of the predictors are useful, the resulting regression rules are more easily interpreted and applied, and may be more accurate in application, since the rules are derived by means of a crossvalidation technique which maximizes their predictive accuracy. The system is evaluated in an empirical study and compared to traditional regression and CART systems.