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An Introduction to Recursive Partitioning Using the RPART Routines

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TLDR
The tree is constructed: Splitting criteria, building the tree, variable importance, and more.
Abstract
3 Building the tree 5 3.1 Splitting criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.2 Incorporating losses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2.1 Generalized Gini index . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2.2 Altered priors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3 Example: Stage C prostate cancer (class method) . . . . . . . . . . . . . . 10 3.4 Variable importance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

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References
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Book

Classification and regression trees

Leo Breiman
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Journal ArticleDOI

Martingale-based residuals for survival models

TL;DR: In this paper, a set of n independent subjects such that the counting process Ni {Ni(t), t } O} for the ith subject in the set indicates the number of observed events experienced over time t. The sample paths of the Ni are step functions with jumps of size +1 and with Ni(0) = 0.
Book ChapterDOI

Tree-based models

TL;DR: In this article, the authors describe S functions for tree-based modeling, which is an alternative to linear and additive models for regression problems and to linear logistic and additive logistic models for classification problems.
Journal ArticleDOI

Relative risk trees for censored survival data.

TL;DR: A method is developed for obtaining tree-structured relative risk estimates for censored survival data using a recursive partitioning algorithm that adopts most aspects of the widely used Classification and Regression Tree (CART) algorithm.