期刊名称：International Journal of Research and Innovation in Computer Engineering
电子版ISSN：2249-6580
出版年度：2011
卷号：1
期号：2
页码：39-45
出版社：Innovation Science Publications
摘要：Clustering is generally associated with classification problem. A clustering algorithm is used to partition data set into several groups such that the similarity within a group is larger than among groups. This paper presents the two different clustering algorithms and their comparison. First clustering algorithm is based on Fuzzy C-mean clustering, and second algorithm is based on Kernel Fuzzy C-means Clustering. Results show that KFCM is better than FCM as it is extension of FCM but suffers from the overlapping problem. In this paper a new algorithm has been designed and proposed to remove this problem. A comparison of two different clustering techniques is presented by validity indices, Fuzzy C-means clustering and Fuzzy Clustering Subtractive.
关键词：Fuzzy logic; Data Clustering; FCM; Kernel FCM Clustering.
