International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Shyi-Ming Chena∗ and Cheng-Hao Yub

a Department of Computer Science and Information Engineering,National Taiwan University of Science and Technology,Taipei 106, Taiwan, R. O. C.
b Department of Electronic Engineering,National Taiwan University of Science and Technology,Taipei 106, Taiwan, R. O. C.


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ABSTRACT


It is obvious that fuzzy classification systems are important applications of the fuzzy set theory. Fuzzy classification systems can deal with perceptual uncertainties in classification problems. In recent years, many methods have been proposed to deal with fuzzy classification problems. In this paper, we present a new method to deal with the Iris data classification problem based on the concept of fuzzy compatibility relations for finding the cluster centers of training instances. The proposed method can get a higher average classification accuracy rate to deal with the Iris data classification problem than the existing methods.


Keywords: clustering techniques; fuzzy classification systems; fuzzy relations; fuzzy sets; Iris data.


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ARTICLE INFORMATION




Accepted: 2003-12-23
Publication Date: 2004-03-02


Cite this article:

Chen, S.-M.,Yu, C.-H. 2004. A new method for handling fuzzy classification problems Using clustering techniques. International Journal of Applied Science and Engineering, 2, 90–107. https://doi.org/10.6703/IJASE.2004.2.(1).90


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