On the number of groups in clustering

Clustering is the problem of partitioning data into a finite number k of homogeneous and separate groups, called clusters. A good choice of k is essential for building meaningful clusters. In this paper, this task is addressed from the point of view of model selection via penalization. We design an appropriate penalty shape and derive an associated oracle-type inequality. The method is illustrated on both simulated and real-life data sets.

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Year of publication:	2011
Authors:	Fischer, Aurélie
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 81.2011, 12, p. 1771-1781
Publisher:	Elsevier
Subject:	k-means clustering \| Number of clusters \| Model selection \| Oracle inequality \| Slope heuristics

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010576135