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17

ICML
2005
IEEE

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Error bounds for correlation clustering

14 years 5 months ago

Error bounds for correlation clustering

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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

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Correlation Clustering | Correlation Clustering Scales | ICML 2005 | Machine Learning | Planted Partition Model |

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Added	17 Nov 2009
Updated	17 Nov 2009
Type	Conference
Year	2005
Where	ICML
Authors	Thorsten Joachims, John E. Hopcroft

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