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Towards a standard methodology to evaluate internal cluster validity indices

机译:建立评估内部聚类有效性指标的标准方法

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摘要

The evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.
机译:内部聚类有效性指标的评估和比较是聚类领域的关键问题。大多数评估中使用的方法均假设聚类算法正确运行。我们提出了一种替代方法,该方法不会做出经常错误的假设。我们比较了两种方法的7个内部聚类有效性指标,得出的结论是,所提出的方法所获得的结果更能代表比较指标的实际能力。

著录项

  • 来源
    《Pattern recognition letters》 |2011年第3期|p.505-515|共11页
  • 作者单位

    Department of Computer Architecture and Technology, University of the Basque Country, 20018 Donostia, Spain;

    Department of Computer Architecture and Technology, University of the Basque Country, 20018 Donostia, Spain;

    Department of Computer Architecture and Technology, University of the Basque Country, 20018 Donostia, Spain;

    Department of Computer Architecture and Technology, University of the Basque Country, 20018 Donostia, Spain;

    Department of Computer Architecture and Technology, University of the Basque Country, 20018 Donostia, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cluster validation; Cluster validity index; Unsupervised learning;

    机译:聚类验证;聚类有效性指数;无监督学习;

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