The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Optimal partitioning for classification and regression trees
Abstract
An iterative algorithm that finds a locally optimal partition for an arbitrary loss function, in time linear in N for each iteration is presented. The algorithm is a K-means-like clustering algorithm that uses as its distance measure a generalization of Kullback's information divergence. Moreover, it is proven that the globally optimal partition must satisfy a nearest neighbour condition using divergence as the distance measure. These results generalize similar results of L. Breiman et al. (1984) to an arbitrary number of classes or regression variables and to an arbitrary number of bills. Experimental results on a text-to-speech example are provided and additional applications of the algorithm, including the design of variable combinations, surrogate splits, composite nodes, and decision graphs, are suggested.>
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Cites
Quinlan, J. R. (1986) · Machine Learning · doi:10.1007/bf00116251 · Cited by 21,439
An Algorithm for Vector Quantizer Design
Linde, Y., Buzo, A., & Gray, R. (1980) · IEEE Transactions on Communications · doi:10.1109/tcom.1980.1094577 · Cited by 7,201
Cover, T. M. (1965) · IEEE Transactions on Electronic Computers · doi:10.1109/pgec.1965.264137 · Cited by 2,044
Constructing optimal binary decision trees is NP-complete
Hyafil, L., & Rivest, R. L. (1976) · Information Processing Letters · doi:10.1016/0020-0190(76)90095-8 · Cited by 959
Cited by
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Murthy, S. K. (1998) · Data Mining and Knowledge Discovery · doi:10.1023/a:1009744630224 · Cited by 991
Discretization: An Enabling Technique
Liu, H., Hussain, F., Tan, C. L., & Dash, M. (2002) · Data Mining and Knowledge Discovery · doi:10.1023/a:1016304305535 · Cited by 981
Fifty Years of Classification and Regression Trees
Loh, W. (2014) · International Statistical Review · doi:10.1111/insr.12016 · Cited by 649
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning
Garcia, S., Luengo, J., Sáez, J. A., López, V., & Herrera, F. (2013) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2012.35 · Cited by 548
An active testing model for tracking roads in satellite images
Geman, D., & Jedynak, B. (1996) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.476006 · Cited by 498
Metadata
- Authors
- Chou, P. A.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1991-04
- Volume
- 13
- Issue
- 4
- Pages
- 340-354
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2080209778
- Cited by
- 248
- References
- 4
- FWCI
- 18.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chou, P. A. (1991). Optimal partitioning for classification and regression trees. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.88569
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
