A New Method for Handling Fuzzy Classification Problems Using Clustering Techniques
Shyi‐Ming Chen, CHENG-HAO YU · 2004
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.