CVAP: Validation for Cluster Analyses

DOI 11 References
  • Wang Kaijun
    School of Mathematics and Computer Science, Fujian Normal University
  • Wang Baijie
    School of Computer Science and Technology, Xidian University
  • Peng Liuqing
    School of Computer Science and Technology, Xidian University

Description

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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Details 詳細情報について

  • CRID
    1390282680212076416
  • NII Article ID
    130000402596
  • DOI
    10.2481/dsj.007-020
  • ISSN
    16831470
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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