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A Classifier Based on Neuro-Fuzzy Inference System Ernest
Czogala*, Jacek Leski*, and Yoichi Hayashi**
*Institute of Electronics, Technical University of Silesia Akademicka 16, 44-101 Gliwice, Poland
**Department of Computer Science, Meiji University 1-1-1 Higashimita, Tama-ku, Kawasaki 214-8571, Japan
Received:January 10, 1999Accepted:June 21, 1999Published:August 20, 1999
Keywords:Neuro-fuzzy inference system, If-then rules, Fuzzy classifier, Pattern recognition
Abstract
In this paper a new classifier based on fuzzy inference system has been described. The novelty of the classifier consists in the moving fuzzy consequent in if-then rules and in selection method of target values for classifier outputs minimizing the number of false classifications. The location of fuzzy set in conclusion is determined by a linear combination of system inputs. The method of classifier construction for two classes and an extension for a greater number of classes has been presented. The tests of the new classifier are carried out on the basis of the data bases known from literature: forensic glass and iris.
Cite this article as:Czogala, J. Leski, and Y. Hayashi, “A Classifier Based on Neuro-Fuzzy Inference System Ernest,” J. Adv. Comput. Intell. Intell. Inform., Vol.3 No.4, pp. 282-288, 1999.Data files:
