Chunk #129 — Features and Pitfalls — Bias in Variable Selection and Variable Importance

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An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

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The functions tree (Ripley 2007) and rpart (Therneau and Atkinson. 2006) for trees and random-Forest (Breiman, Cutler, Liaw, and Wiener 2006; Liaw and Wiener 2002) for bagging and random forests, on the other hand, that resemble the original CART and random forests algorithms more closely, induce variable selection bias and are not suggested when the data set contains predictor variables of different types.