Fuzzy rules generation method for classification problems using rough sets and genetic algorithms

Authors:
Marek Sikora
Affiliations:
Institute of Computer Sciences, Silesian University of Technology, Gliwice, Poland
Venue:
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Year:
2005

Citing 2
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Abstract

A method of constructing a classifier that uses fuzzy reasoning is described in this paper. Rules for this classifier are obtained by means of algorithms relying on a tolerance rough sets model. Got rules are in so called sharp” form, a genetic algorithm is used for fuzzification of these rules. Presented results of experiments show that the proposed method allows getting a smaller rules set with similar (or better) classification abilities.