Generalized information theoretic cluster validity indices for soft clusterings

Yang Lei, J. Bezdek, Jeffrey Chan, X. Nguyen, Simone Romano, J. Bailey
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引用次数: 13

Abstract

There have been a large number of external validity indices proposed for cluster validity. One such class of cluster comparison indices is the information theoretic measures, due to their strong mathematical foundation and their ability to detect non-linear relationships. However, they are devised for evaluating crisp (hard) partitions. In this paper, we generalize eight information theoretic crisp indices to soft clusterings, so that they can be used with partitions of any type (i.e., crisp or soft, with soft including fuzzy, probabilistic and possibilistic cases). We present experimental results to demonstrate the effectiveness of the generalized information theoretic indices.
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广义信息理论的软聚类有效性指标
已有大量的外部效度指标被提出用于聚类效度。其中一类聚类比较指标是信息理论测度,由于其强大的数学基础和检测非线性关系的能力。然而,它们是为评估脆(硬)分区而设计的。本文将8个信息论脆指标推广到软聚类中,使得它们可以用于任何类型的分区(即脆或软,软包括模糊情况、概率情况和可能性情况)。实验结果证明了广义信息论指标的有效性。
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