Modified Gustafson-Kessel clustering on medical diagnostic systems

Mostly Clustering methods are not supervised methods those can be applied to the data to arrange them into groups based on a feature called similarity among the individual data items. In this study, Modified Gustafson-Kessel (MGK) clustering technique is applied to group the patients into different thyroid diseases´ clusters. Further, the results of Modified Gustafson-Kessel clustering algorithm and Fuzzy c-Means (FCM) clustering algorithm are compared according to the classification performance. These results show that Modified Gustafson-Kessel clustering algorithm gives better performance.