Comparison of Imputation Strategies in FNM-based and RFCM-based Fuzzy Co-Clustering

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 highest value of the normalized mutual information than others.