Application of xie-beni-type validity index to fuzzy co-clustering models based on cluster aggregation and pseudo-cluster-center estimation
Mai Muranishi, Katsuhiro Honda, Akira Notsu · 2014
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.