rpart Decision Tree Learning Algorithm
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An rpart Decision Tree Learning Algorithm is a Decision Tree Learning Algorithm(s) based on the CART Algorithms.
- Context:
- It can be implemented into an rpart Decision Tree Learning System.
- See: C4.5 Decision Tree Learning Algorithm.
References
2011
- (Therneau & Atkinson, 2011) ⇒ Terry M. Therneau, and Elizabeth J. Atkinson. (2011). “An Introduction to Recursive Partitioning Using the RPART Routines." Mayo Foundation Technical Report.
- QUOTE: This document is an update of a technical report written several years ago at Stanford [6], and is intended to give a short overview of the methods found in the rpart routines, which implement many of the ideas found in the CART (Classification and Regression Trees) book and programs of Breiman, Friedman, Olshen and Stone [1]. Because CART is the trademarked name of a particular software implementation of these ideas, and tree has been used for the S-plus routines of Clark and Pregibon ∼[3] a different acronym — Recursive PARTitioning or rpart — was chosen.