The construction of multiple partitions in consensus clustering with random initialization and various parameters values of clustering algorithm enable us to measure the stability of objects (points) in a cluster. The procedure to indicate stability is aided by the co-occurrences of pair objects (i,j) allocated to the same cluster in each partition. In this paper, we propose a voting-merged method - a combination of voting-based method and merging process. Our experiment with simulations and real datasets shows better performance for well-separated clusters and low degree of overlapping.
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