Ensemble clustering based on evidence extracted from the co-association matrix

This paper removes multiple level evidences having low occurrence frequencies from the co-association matrix, and uses normalized cut to achieve multiple clustering results, demonstrating that the proposed scheme outperforms some state-of-the-art clustering ensemble approaches.