期刊名称：International Journal of Computer and Information Technology
印刷版ISSN：2279-0764
出版年度：2013
卷号：2
期号：4
页码：663
出版社：International Journal of Computer and Information Technology
摘要：Semi-supervised clustering is an important method which can improve clustering performance by introducing partial supervised information. This paper mainly studies the semi-supervised fuzzy clustering based on Mahalanobis distance and Gaussian Kernel for SCAPC algorithm. Here, we give a new semi-supervised fuzzy clustering objective function. By solving the optimization problem with above objective function, we obtain a semi-supervised fuzzy clustering algorithm F-SCAPC which includes F(M)-SCAPC and F(K)-SCAPC. And we do experimental research for proposed algorithm F-SCAPC using the selected standard data set and the artificial data set. Besides, we compare performance of presented algorithm F-SCAPC with one of FCM, CA, AFFC, KCA, KFCM-F and SCAPC algorith ms. From the results, we can see that F-SCAPC is effective in the convergence speed and the clustering accuracy
