CVAP: Validation for Cluster Analyses

Authors

Kaijun Wang School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, P. R. China
Baijie Wang School of Computer Science and Technology, Xidian University, Xian 710071, P. R. China.
Liuqing Peng School of Computer Science and Technology, Xidian University, Xian 710071, P. R. China.

DOI:

Keywords:

Cluster validation, Validity indices, Visual cluster analysis environment

Abstract

Evaluation of clustering results (or cluster validation) is an important and necessary step in cluster analysis, but it is often time-consuming and complicated work. We present a visual cluster validation tool, the Cluster Validity Analysis Platform (CVAP), to facilitate cluster validation. The CVAP provides necessary methods (e.g., many validity indices, several clustering algorithms and procedures) and an analysis environment for clustering, evaluation of clustering results, estimation of the number of clusters, and performance comparison among different clustering algorithms. It can help users accomplish their clustering tasks faster and easier and help achieve good clustering quality when there is little prior knowledge about the cluster structure of a data set.

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Published

2009-04-24

Issue

Vol. 8 (2009)

Section

Research Papers

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