Publikation: Subsampling Conflicts to Construct Better Fuzzy Rules
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Many fuzzy rule induction algorithms have been proposed during the past decade or so. Most of these algorithms tend to scale badly with large dimensions of the feature space because the underlying heuristics tend to constrain suboptimal features. Often noisy training instances also influence the size of the resulting rule set. In this paper an algorithm is discussed that extracts a set of so called mixed fuzzy rules. These rules can be extracted from feature spaces with diverse types of attributes and handle the corresponding different types of constraints in parallel. The underlying heuristic minimizes the loss of coverage for each rule when a conflict occurs. We present the original algorithm, which voids conflicts for each pattern individually and demonstrate how a subsampling trategy improves the resulting rule set, both with respect to performance and nterpretability of the resulting rules.
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BERTHOLD, Michael R., 2001. Subsampling Conflicts to Construct Better Fuzzy Rules. 9th IFSA and 20th NAFIPS. Vancouver, British Columbia, Canada, 25. Juli 2001 - 28. Juli 2001. In: Joint 9th IFSA World congress and 20th NAFIPS internat. conf., Vancouver, British Columbia, Canada, July 25 - 28, 2001. 2001, pp. 1098-1103BibTex
@inproceedings{Berthold2001Subsa-5432, year={2001}, title={Subsampling Conflicts to Construct Better Fuzzy Rules}, booktitle={Joint 9th IFSA World congress and 20th NAFIPS internat. conf., Vancouver, British Columbia, Canada, July 25 - 28, 2001}, pages={1098--1103}, author={Berthold, Michael R.} }
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