ROC Analysis of FCM Classifier With Cauchy Weight

抄録

A postsupervised FCMclassifier using a modified Cauchy weight as a membership function has been proposed. The performances of the classifier in terms of ROC and rejection curves are compared by using the benchmark datasets of the UCI ML repository. Cauchy weight function gives lower confidence to the classification decision and this distinguishes the FCM classifier from the Gaussian classifier. The FCM classifier outperforms the Gaussian classifier and the k-nearest neighbor classifier on many datasets in general.