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In this paper, we propose a new consensus clustering algorithm, which is based on an existing clustering paradigm, called enhanced splitting merging awareness tactics (E-SMART). The problem of determining the number of clusters, which affects many state-of-theart consensus clustering algorithms, is addressed by the proposed CoCE-SMART algorithm. The idea behind CoCE-SMART is that SMART is used repeatedly...
The recently proposed UNCLES method has the ability to unify clustering results from multiple datasets under different types of external specifications. It can also tunably tighten the results such that many objects are unassigned from all of the clusters to obtain few tight clusters. Despite the success of this method, setting its parameters, such as the number of clusters (K) and the tuning parameters...
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