Title :
Comparison of imputation strategies in FNM-based and RFCM-based fuzzy co-clustering
Author_Institution :
Shibaura Inst. of Technol., Tokyo, Japan
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.
Keywords :
entropy; fuzzy set theory; matrix algebra; minimax techniques; pattern clustering; FNM-based fuzzy coclustering; RFCM-based fuzzy coclustering; augmented dissimilarity matrix; eRFCM-based method; entropy regularization; fuzzifier parameter setting; imputation strategies; minimax version; normalized mutual information; triangle inequality-based approximation;
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-2742-8
DOI :
10.1109/SCIS-ISIS.2012.6505051