# 1984 ClassificationAndRegressionTrees

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- (Breiman et al., 1984) ⇒ Leo Breiman, Jerome H. Friedman, Charles J. Stone, and R. A. Olshen. (1984). “Classification and Regression Trees.” Chapman & Hall. ISBN:0412048418

**Subject Headings:** CART Algorithm, Gini Index.

## Notes

## Cited By

### 2004

- (Raileanu & Stoffel, 2004) ⇒ Laura Elena Raileanu, and Kilian Stoffel. (2004). “Theoretical Comparison between the Gini Index and Information Gain Criteria.” In: Annals of Mathematics and Artificial Intelligence, 41(1). doi:10.1023/B:AMAI.0000018580.96245.c6

### 1999

- (Torgo, 1999) ⇒ Luis Torgo. (1999). “Inductive Learning of Tree-based Regression Models.” Ph.D. Thesis, Thesis, Faculty of Sciences, University of Porto
- QUOTE: Least squares (LS) regression trees had already been described in detail in the book by Breiman et. al. (1984).

### 1993

- (Quinlan, 1993a) ⇒ J. Ross Quinlan. (1993). “C4.5: Programs for machine learning.” Morgan Kaufmann. ISBN:1558602380

## Quotes

### Book Overview

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.

## References

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