Possibilistic Fuzzy C-means clustering on medical diagnostic systems

Abstract

Classification or Clustering is the task of grouping similar objects based on the similarity among the individuals. The techniques using in clustering are mostly unsupervised methods. In this study, Possibilistic Fuzzy C-means (PFCM) clustering technique is used to classify the patients into different clusters of thyroid diseases. Further, the results of Possibilistic Fuzzy C-means clustering algorithm and Fuzzy c-Means clustering (FCM) algorithm are compared according to the classification performance. The results exhibit that the Possibilistic Fuzzy C-means clustering algorithm performs well.