Fuzzy clustering ensemble by optimization approach based on clustering reliability.

Although some ensemble clustering approaches have been developed in recent years to improve the quality of the clustering, but lack of a median fuzzy partition-based consensus function that considers more participate reliable fuzzy clustering, remains unsolved problem. In this paper, we convert the median fuzzy partition problem into an optimization problem based on the reliability-based co-association matrix that minimizes distances between coassociation matrix of final clustering and co-association matrix of base-clustering in the ensemble. The optimization problem is a constrained nonlinear objective function and we solve it by sparse sequential quadratic programming (SSQP). Experimental results reveal the effectiveness of the proposed approach rather than the state-of-the-art methods in the qualityterms on various standard datasets. [ABSTRACT FROM AUTHOR]