ML Anthology

Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)

Alípio Jorge, Pavel Brazdil
ECML-PKDD 1995 pp. 299-302
doi:10.1007/3-540-59286-5_72 /ecmlpkdd/1995/jorge1995ecml-learning/

Abstract

In this paper we are concerned with the problem of inducing recursive Horn clauses from small sets of training examples. The method of iterative bootstrap induction is presented. In the first step, the system generates simple clauses, which can be regarded as properties of the required definition. Properties represent generalizations of the positive examples, simulating the effect of having larger number of examples. Properties are used subsequently to induce the required recursive definitions. This paper describes the method together with a series of experiments. The results support the thesis that iterative bootstrap induction is indeed an effective technique that could be of general use in ILP.

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Cite

Text

Jorge and Brazdil. "Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)." European Conference on Machine Learning, 1995. doi:10.1007/3-540-59286-5_72

Markdown

[Jorge and Brazdil. "Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)." European Conference on Machine Learning, 1995.](https://mlanthology.org/ecmlpkdd/1995/jorge1995ecml-learning/) doi:10.1007/3-540-59286-5_72

BibTeX

@inproceedings{jorge1995ecml-learning,
  title     = {{Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)}},
  author    = {Jorge, Alípio and Brazdil, Pavel},
  booktitle = {European Conference on Machine Learning},
  year      = {1995},
  pages     = {299-302},
  doi       = {10.1007/3-540-59286-5_72},
  url       = {https://mlanthology.org/ecmlpkdd/1995/jorge1995ecml-learning/}
}