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Cited by 499

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Classification and Regression Trees

·2022·The R Book

Abstract

Classification and regression tree models (CARTs) are computationally intensive methods that are used in situations where there are many explanatory variables and user would like guidance about, possibly, including them in the model: classification trees are where the outcome is discrete and regression trees where the outcome is continuous. A CART model is fitted using binary recursive partitioning, whereby the data are successively split along co-ordinate axes of each of the explanatory variables so that, at any node, the split which maximally distinguishes the response variable in the left and the right branches is selected. Classification trees, for discrete outcomes, are derived using the same R functions as for regression trees.

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Metadata

Venue
The R Book
Publisher
Wiley
Published
2022-09-09
Pages
761-777
OpenAlex
W2607893089
Cited by
499
References
1
Type
other
Language
en
Open access
closed

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CoChat. (2026). Citation check: Classification and Regression Trees. https://app.cochat.ai/papers/10.1002/9781119634461.ch20
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Classification and Regression Trees. (2022). The R Book. https://doi.org/10.1002/9781119634461.ch20

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