A CLUSTER VALIDITY INDEX BASED ON FUZZY HYBRID HIERARCHICAL CLUSTERING

摘要：

A novel cluster validity index is proposed for the validation of partitions for object data. The cluster validity index ranges from the creation of the subclasses produced by the fuzzy c-means algorithm up to their fusion which implies proximity tree according to the largest separation criterion. Testing of the proposed index and four previously formulated indices on well-known data sets shows the superior effectiveness and reliability of the proposed index in comparison with other indices.

关键词： Fuzzy clustering Cluster validity Hierarchical classification Fuzzy c-means

作者: WEINA WANG YING ZHAO

作者单位: Jilin Institute of Chemical Technology, Chengde Street No.45, Jilin Province, China

会议类型: 国际会议

会议名称: The Second International Conference on Information & Systems Sciences(ICISS2008)(第二届信息与系统科学国际会议)

会议地点: 大连

会议语种:英文

页码: 946-953

在线出版日期: 2008-12-18（万方平台首次上网日期，不代表论文的发表时间）