Dissimilarity Clustering by Hierarchical Multi-Level Refinement

04/29/2012
by   Brieuc Conan-Guez, et al.
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We introduce in this paper a new way of optimizing the natural extension of the quantization error using in k-means clustering to dissimilarity data. The proposed method is based on hierarchical clustering analysis combined with multi-level heuristic refinement. The method is computationally efficient and achieves better quantization errors than the

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