Determining the Number of Clusters via Iterative Consensus Clustering

5 Aug 2014 Shaina Race Carl Meyer Kevin Valakuzhy

We use a cluster ensemble to determine the number of clusters, k, in a group of data. A consensus similarity matrix is formed from the ensemble using multiple algorithms and several values for k. A random walk is induced on the graph defined by the consensus matrix and the eigenvalues of the associated transition probability matrix are used to determine the number of clusters... (read more)

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