A Kernel Fuzzy Classifier with KFCMC and GA

Author

Chen, Xuri ; Xu, Weimin

Author_Institution

Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai

Volume

1

fYear

2008

fDate

17-18 Oct. 2008

Firstpage

162

Lastpage

165

Abstract

A kernel fuzzy classifier with KFCMC and GA is proposed in this paper. For such classifier, firstly, the original sample space is mapped into a high dimensional feature space by selecting appropriate kernel function. Then in the feature space, training samples are divided into some clusters by proposed KFCMC algorithm. For each created cluster, a fuzzy rule is defined. Some parameters of fuzzy classifier are selected by GAs. The proposed constructing classifier method is detailedly introduced, and the experiment results and the comparison results with the similar approach are provided. Experiment results show the proposed fuzzy classifier has very high classification accuracy and has the better applied values.

Keywords

fuzzy set theory; genetic algorithms; learning (artificial intelligence); pattern classification; pattern clustering; K-fuzzy C-means clustering algorithm; genetic algorithm; high-dimensional feature space; kernel fuzzy rule classifer; training sample; Clustering algorithms; Clustering methods; Computational intelligence; Design engineering; Electronic mail; Fuzzy neural networks; Fuzzy set theory; Kernel; Neural networks; Unsupervised learning; Genetic Algorithm (GA); Kernel Function; Kernel Fuzzy C-means Clustering (KFCMC); Kernel Fuzzy Classifier;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design, 2008. ISCID '08. International Symposium on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3311-7

Type

conf

DOI

10.1109/ISCID.2008.124

Filename

4725581