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Cluster Editing

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The Cluster Editing problem is almost equivalent to Correlation Clustering on complete instances. The idea is to obtain a graph that consists only of cliques. Although Cluster Deletion requires us to delete the smallest number of edges to obtain such a graph, in Cluster Editing we are permitted to add as well as remove edges. The final variant is Cluster Completion in which edges can only be added: each of these problems can be restricted to building a specified number of cliques.

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© 2017 Springer Science+Business Media New York

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(2017). Cluster Editing. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_121

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