Cluster Ensemble with Averaged Co-Association Matrix Maximizing the Expected Margin
نویسنده
چکیده
The problem considered is cluster analysis with usage of the ensemble approach. The paper proposes a method for finding optimal weights for the averaged co-association matrix applied to the construction of the ensemble partition. The main idea is to find such weights for which the expectation of ensemble margin takes its maximum value. A latent variable pairwise classification model is used for determining margin characteristics dependent on cluster validity indices. To construct the ensemble partition, we apply minimum spanning tree found on the averaged co-association matrix as an adjacency matrix. The efficiency of the method is confirmed by Monte-Carlo simulations with artificial data sets.
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