Comparison of imputation strategies in FNM-based and RFCM-based fuzzy co-clustering

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, some imputation strategies are compared in the point that the block diagonal part of the augmented dissimilarity matrix must be filled in for FNM-based and RFCM-based fuzzy co-clustering by entropy regularization, By numerical experiment, the eRFCM-based method with the minimax version of the strategy of the triangle inequality-based approximation and with higher fuzzifier parameter setting achieves the higher value of the normalized mutual information than others.

Original languageEnglish
Title of host publication6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Pages1988-1993
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe
Duration: 2012 Nov 202012 Nov 24

Other

Other2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
CityKobe
Period12/11/2012/11/24

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Kanzawa, Y. (2012). Comparison of imputation strategies in FNM-based and RFCM-based fuzzy co-clustering. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 (pp. 1988-1993). [6505051] https://doi.org/10.1109/SCIS-ISIS.2012.6505051