ML Anthology

The Induction of Probabilistic Rule Sets - The Itrule Algorithm

Rodney M. Goodman, Padhraic Smyth
ICML 1989 pp. 129-132
doi:10.1016/B978-1-55860-036-2.50040-0 /icml/1989/goodman1989icml-induction/

Abstract

In this paper we address the problem of learning sets of probabilistic rules. While attention has been focused for some time now on the learning of fixed classification rule structures such as decision trees, the problem of identifying useful sets of probabilistic production rules is relatively new. We discuss our recent work in this area and conclude that learning and inference algorithms need to be more closely coupled.

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Cite

Text

Goodman and Smyth. "The Induction of Probabilistic Rule Sets - The Itrule Algorithm." International Conference on Machine Learning, 1989. doi:10.1016/B978-1-55860-036-2.50040-0

Markdown

[Goodman and Smyth. "The Induction of Probabilistic Rule Sets - The Itrule Algorithm." International Conference on Machine Learning, 1989.](https://mlanthology.org/icml/1989/goodman1989icml-induction/) doi:10.1016/B978-1-55860-036-2.50040-0

BibTeX

@inproceedings{goodman1989icml-induction,
  title     = {{The Induction of Probabilistic Rule Sets - The Itrule Algorithm}},
  author    = {Goodman, Rodney M. and Smyth, Padhraic},
  booktitle = {International Conference on Machine Learning},
  year      = {1989},
  pages     = {129-132},
  doi       = {10.1016/B978-1-55860-036-2.50040-0},
  url       = {https://mlanthology.org/icml/1989/goodman1989icml-induction/}
}