The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Classification and Regression Trees.
Abstract
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.
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Metadata
- Authors
- Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1984-09
- Volume
- 40
- Issue
- 3
- Pages
- 874
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W1594031697
- Cited by
- 23,522
- References
- 15
- FWCI
- 62.48
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
