文章基本信息

标题：Deterministic Annealing Framework in MMMs-Induced Fuzzy Co-Clustering and Its Applicability
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作者：Shunnya Oshio ; Katsuhiro Honda ; Seiki Ubukata 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2016
卷号：16
期号：1
页码：43-50
出版社：International Journal of Computer Science and Network Security
摘要：Initialization problem is a significant issue in FCM-type clustering models, in which alternative optimization is often started with random initial partitions and can be trapped into local optima caused by bad initialization. The deterministic clustering approach is a practical procedure for utilizing a robust feature of very fuzzy partitions and tries to converge the iterative FCM process to a plausible solution by gradually decreasing the fuzziness degree. In this paper, the initialization sensitivity issue is considered in multinomial mixture models-induced fuzzy co-clustering context and a new approach for implementing the deterministic annealing mechanism to fuzzy co-clustering is proposed. The advantages of the proposed approach against the conventional statistical co-clustering model are demonstrated through some numerical experiments.
关键词：Fuzzy co-clustering; Multinomial mixture; Deterministic annealing;��Initialization��problem.