Abstract:

A new fuzzy C-means clustering algorithm was proposed by  the introduction of functions of separation between clusters into FCM clustering algorithm and with the nature of semisupervised learning considered. The model of semisupervised FCM clustering algorithm with the information entropy as constraints was established and the solution to the model was derived. The simulation experiments were performed on UCI data sets to verify the effectiveness of the proposed algorithm. The experimental results show that this modified algorithm gets the better validity and performance.

Key words: semisupervised clustering, fuzzy C-means algorithm (FCM), information entropy