Abstract
An ensemble clustering method is proposed that is based on a weight averaged co-association matrix. The ensemble includes various cluster analysis algorithms whose weights are calculated with the use of cluster validity indices. The properties of the ensemble are analyzed, a probabilistic model is described by which the relations between the characteristics of the ensemble and a quality estimate of a decision are determined, and a method is proposed for determining the optimal weights. The efficiency of the method is analyzed by statistical simulation.
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