VI-Cut is a novel approach for decomposing a hierarchical clustering into the clusters that optimally match a set of known annotations, as measured by the variation of information metric.
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VI-Cut: Finding Biologically Accurate Clusterings in Hierarchical Tree Decompositions Using the Variation of Information
Saket Navlakha, James White, Niranjan Nagarajan, Mihai Pop, Carl Kingsford
Research in Computational Molecular Biology
Lecture Notes in Computer Science Volume 5541, 2009, pp 400-417