Generalized Recursive Splitting Algorithms for Learning Hybrid Concepts

Lambert, Bruce L.; Tcheng, David K.; Lu, Stephen C. Y.

doi:10.1016/B978-1-55860-036-2.50129-6

Generalized Recursive Splitting Algorithms for Learning Hybrid Concepts

Bruce L. Lambert, David K. Tcheng, Stephen C. Y. Lu

ICML 1989 pp. 496-498

doi:10.1016/B978-1-55860-036-2.50129-6 /icml/1989/lambert1989icml-generalized/

Abstract

This paper describes the Competitive Relation Learner (CRL), a generalized recursive splitting algorithm capable of producing a wide range of hybrid concept representations through the competitive application of multiple learning strategies, multiple decomposition strategies, and multiple decomposition evaluation strategies. Experimental results are reported that demonstrate CRL's ability to outperform several well known fixed-bias strategies.

ICML Semantic Scholar

Cite

Text

Lambert et al. "Generalized Recursive Splitting Algorithms for Learning Hybrid Concepts." International Conference on Machine Learning, 1989. doi:10.1016/B978-1-55860-036-2.50129-6

Markdown

[Lambert et al. "Generalized Recursive Splitting Algorithms for Learning Hybrid Concepts." International Conference on Machine Learning, 1989.](https://mlanthology.org/icml/1989/lambert1989icml-generalized/) doi:10.1016/B978-1-55860-036-2.50129-6

BibTeX

@inproceedings{lambert1989icml-generalized,
  title     = {{Generalized Recursive Splitting Algorithms for Learning Hybrid Concepts}},
  author    = {Lambert, Bruce L. and Tcheng, David K. and Lu, Stephen C. Y.},
  booktitle = {International Conference on Machine Learning},
  year      = {1989},
  pages     = {496-498},
  doi       = {10.1016/B978-1-55860-036-2.50129-6},
  url       = {https://mlanthology.org/icml/1989/lambert1989icml-generalized/}
}