A Fuzzy Co-Clustering Algorithm via Modularity Maximization

Abstract EN

In this paper we propose a fuzzy co-clustering algorithm via modularity maximization, named MMFCC.

In its objective function, we use the modularity measure as the criterion for co-clustering object-feature matrices.

After converting into a constrained optimization problem, it is solved by an iterative alternative optimization procedure via modularity maximization.

This algorithm offers some advantages such as directly producing a block diagonal matrix and interpretable description of resulting co-clusters, automatically determining the appropriate number of final co-clusters.

The experimental studies on several benchmark datasets demonstrate that this algorithm can yield higher quality co-clusters than such competitors as some fuzzy co-clustering algorithms and crisp block-diagonal co-clustering algorithms, in terms of accuracy.