A modified pittsburg approach to design a genetic fuzzy rule-based classifier from data

Authors:
Marian B. Gorzałczany;Filip Rudziński
Affiliations:
Department of Electrical and Computer Engineering, Kielce University of Technology, Kielce, Poland;Department of Electrical and Computer Engineering, Kielce University of Technology, Kielce, Poland
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Year:
2010

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Abstract

The paper presents a modification of the Pittsburg approach to design a fuzzy classifier from data. Original, non-binary crossover and mutation operators are introduced. No special coding of fuzzy rules and their parameters is required. The application of the proposed technique to design the fuzzy classifier for the well known benchmark data set (Wisconsin Breast Cancer) available from the http://archive.ics.uci.edu/ml is presented. A comparative analysis with several alternative (fuzzy) rule-based classification techniques has also been carried out.