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ICML
2005
IEEE

Error bounds for correlation clustering

15 years 2 hour ago
Error bounds for correlation clustering
This paper presents a learning theoretical analysis of correlation clustering (Bansal et al., 2002). In particular, we give bounds on the error with which correlation clustering recovers the correct partition in a planted partition model (Condon & Karp, 2001; McSherry, 2001). Using these bounds, we analyze how the accuracy of correlation clustering scales with the number of clusters and the sparsity of the graph. We also propose a statistical test that analyzes the significance of the clustering found by correlation clustering.
Thorsten Joachims, John E. Hopcroft
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2005
Where ICML
Authors Thorsten Joachims, John E. Hopcroft
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