On the Scalability of Evidence Accumulation Clustering

Lourenço, A. ; Fred, A. L. N. ; Jain, A. K.

On the Scalability of Evidence Accumulation Clustering, Proc International Conf. on Pattern Recognition - ICPR, Instanbul, Turkey, Vol. ., pp. 782 - 785, August, 2010.

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Abstract

This work focuses on the scalability of the Evidence Accumulation Clustering (EAC) method. We first address the space complexity of the co-association matrix. The sparseness of the matrix is related to the construction of the clustering ensemble. Using a split and merge strategy combined with a sparse matrix representation, we empirically show that a linear space complexity is achievable in this framework, leading to the scalability of EAC method to clustering large data-sets.

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On the Scalability of Evidence Accumulation Clustering