An Analysis of Stopping and Filtering Criteria for Rule Learning

Fuernkranz Johannes, Peter Flach

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

8 Citations (Scopus)

Abstract

In this paper, we investigate the properties of commonly used pre- pruning heuristics for rule learning by visualizing them in PN-space. PN-space is a variant of ROC-space, which is particularly suited for visualizing the behavior of rule learning and its heuristics. On the one hand, we think that our results lead to a better understanding of the effects of stopping and filtering criteria, and hence to a better understanding of rule learning algorithms in general. On the other hand, we uncover a few shortcomings of commonly used heuristics, thereby hopefully motivating additional work in this area.
Translated title of the contributionAn Analysis of Stopping and Filtering Criteria for Rule Learning
Original languageEnglish
Title of host publicationProceedings of the 15th European Conference on Machine Learning
Pages123-133
Publication statusPublished - 2004

Bibliographical note

ISBN: 3540231056
Publisher: Springer-Verlag
Name and Venue of Conference: Proceedings of the 15th European Conference on Machine Learning
Other identifier: 2000550

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