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CVAP: Validation for Cluster Analyses

Authors:

Kaijun Wang ,

School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, P. R. China
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Baijie Wang,

School of Computer Science and Technology, Xidian University, Xian 710071, P. R. China.
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Liuqing Peng

School of Computer Science and Technology, Xidian University, Xian 710071, P. R. China.
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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.
DOI: http://doi.org/10.2481/dsj.007-020
How to Cite: Wang, K., Wang, B. & Peng, L., (2009). CVAP: Validation for Cluster Analyses. Data Science Journal. 8, pp.88–93. DOI: http://doi.org/10.2481/dsj.007-020
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Published on 24 Apr 2009.
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