A NEW CLUSTERING VALIDITY INDEX FOR EVALUATING ARBITRARY SHAPE CLUSTERS

摘要：

When doing clustering analysis it always needs a clustering validity index to evaluate if the present clustering scheme can reflect the real natural structure of the dataset The clusters founded by the clustering algorithm can be of arbitrary shape, but the exiting validity indices can only assess the validity of convex clusters.To solve this problem a new validity index Comp_Sepa is proposed in this paper, which can evaluate a cluster scheme including both non-convex and convex clusters, and the validity index Comp_Sepa is computed by the minimum-cost spanning tree (MST) of the objects of clusters.Experiments show that the new validity index can evaluate the clustering scheme correctly and effectively.

关键词： Validity index Density-based clustering algorithm MST Clustering analysis

作者: SHANG LIU YA-LOU HUANG

作者单位: Information Science & Technology Department, Tanjin University of Finance and Economics Laboratory of Intelligent Information Processing, NanKai University Tianjin 300222, P.R.CHINA

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 3969-3974

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）