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
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.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.