协贝效度指标在基于聚类聚集和伪聚类中心估计的模糊共聚模型中的应用

2014 14th International Conference on Intelligent Systems Design and Applications Pub Date : 2014-11-01 DOI:10.1109/ISDA.2014.7066274

Mai Muranishi, Katsuhiro Honda, A. Notsu

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引用次数: 5

摘要

在k-均值型聚类中，聚类验证是一个重要的问题，它从不同参数设置的结果中选择多个有效性指标支持的最合理的解决方案。Xie-Beni指数是FCM聚类中常用的有效性指标，它通过考虑分区质量和几何特征来衡量模糊分区的可信程度。本研究利用聚类聚集模型(FCCM和fuzzy CoDoK)和伪聚类中心模型(FSKWIC和SCAD2)等几种模糊共聚类模型，研究了xie - beni型共聚类有效性指标的适用性，并在文档聚类应用中进行了验证。

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Application of xie-beni-type validity index to fuzzy co-clustering models based on cluster aggregation and pseudo-cluster-center estimation

In k-Means-type clustering, cluster validation is an important problem, where the most plausible solution supported by several validity indices is selected from results with various parameter settings. Xie-Beni index is a popular validity index in FCM clustering, which measures the plausibility level of fuzzy partitions by considering partition quality and geometrical features. In this research, the applicability of a Xie-Beni-type co-cluster validity index is studied with several fuzzy co-clustering models such as cluster aggregation models (FCCM and Fuzzy CoDoK) and pseudo-cluster-center models (FSKWIC and SCAD2), and is demonstrated in a document clustering application.

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2014 14th International Conference on Intelligent Systems Design and Applications

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