The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

chapter 1|17 pages


chapter 2|41 pages

Introduction To Tree Classification

chapter 3|34 pages

Right Sized Trees and Honest Estimates

chapter 4|37 pages

Splitting Rules

chapter 5|44 pages

Strengthening and Interpreting

chapter 6|29 pages

Medical Diagnosis and Prognosis

chapter 7|13 pages

Mass Spectra Classification

chapter 8|50 pages

Regression Trees

chapter 9|13 pages

Bayes Rules and Partitions

chapter 10|18 pages

Optimal Pruning

chapter 11|21 pages

Construction of Trees from a Learning Sample

chapter 12|24 pages