Benchmarking parameterized fuzzy c-Means classifier

Abstract

This paper reports on the performance of the fuzzy c-means based classifier (FCMC). Test set performances optimized by way of several CV procedures and three sets of hyperparameters are throughly compared. 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 (k-NN). Randomized test sets performance of the classifier is comparable to that of the support vector machine (SVM) reported in the literature.