Tree-Based Models

Publisher Website
Google Scholar
Abstract
This chapter describes S functions for tree-based modeling. Tree-based models provide an alternative to linear and additive models for regression problems and to linear logistic and additive logistic models for classification problems. The models are fitted by binary recursive partitioning whereby a dataset is successively split into increasingly homogeneous subsets until it is infeasible to continue. The implementation described in this chapter consists of a number of functions for growing, displaying, and interacting with tree-based models. This approach to tree-based models is consistent with the data-analytic approach to other models, and consists primarily of fits, residual analyses, and interactive graphical inspection.

This publication has 0 references indexed in Scilit: