Benchmarking Parameterized Fuzzy c-Means Classifier

Abstract

This paper reports on the performance of the fuzzy c-means based classifier (FCMC) adopting the change rates of mixing proportion of clusters as the free parameters. UCI benchmark datasets are used to evaluate the performance. FCM classifier in combination with standard 10-CV procedure or resubstitution (i.e., 1-CV) procedure for parameter selection achieves good test set performance compared to k-nearest neighbor classifier. Randomized test sets performance of the classifier is comparable to that of the support vector machine (SVM) reported in the literature.