LNCS 2810 A Mixture Model Approach for Binned Data Clustering 1st Edition by Allou Samé, Christophe Ambroise, Gérard Govaert  ISBN 3540452311 9783540452317

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Product details:

ISBN 10: 3540452311

ISBN 13: 9783540452317

Author: Allou Samé, Christophe Ambroise, Gérard Govaert

LNCS 2810 – A Mixture Model Approach for Binned Data Clustering 1st Edition: In some particular data analysis problems, available data takes the form of an histogram. Such data are also called binned data. This paper addresses the problem of clustering binned data using mixture models. A specific EM algorithm has been proposed by Cadez et al.([2]) to deal with these data. This algorithm has the disadvantage of being computationally expensive. In this paper, a classification version of this algorithm is proposed, which is much faster. The two approaches are compared using simulated data. The simulation results show that both algorithms generate comparable solutions in terms of resulting partition if the histogram is accurate enough.

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