Learning Classification Rules Using Bayes

Buntine, Wray L.

doi:10.1016/B978-1-55860-036-2.50033-3

Learning Classification Rules Using Bayes

Wray L. Buntine

ICML 1989 pp. 94-98

doi:10.1016/B978-1-55860-036-2.50033-3 /icml/1989/buntine1989icml-learning/

Abstract

This paper considers the problem of learning classification rules from data in the context of knowledge acquisition. Bayesian theory provides a framework for both designing learning algorithms and for approaching specific learning applications, for instance, in the selection and tuning of learning tools. Experiments are reported demonstrating how this can be done using two well known learning approaches: simple Bayes classifiers and decision trees.

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Cite

Text

Buntine. "Learning Classification Rules Using Bayes." International Conference on Machine Learning, 1989. doi:10.1016/B978-1-55860-036-2.50033-3

Markdown

[Buntine. "Learning Classification Rules Using Bayes." International Conference on Machine Learning, 1989.](https://mlanthology.org/icml/1989/buntine1989icml-learning/) doi:10.1016/B978-1-55860-036-2.50033-3

BibTeX

@inproceedings{buntine1989icml-learning,
  title     = {{Learning Classification Rules Using Bayes}},
  author    = {Buntine, Wray L.},
  booktitle = {International Conference on Machine Learning},
  year      = {1989},
  pages     = {94-98},
  doi       = {10.1016/B978-1-55860-036-2.50033-3},
  url       = {https://mlanthology.org/icml/1989/buntine1989icml-learning/}
}