Finding the number of disparate clusters with background contamination

Atkinson, Anthony C., Cerioli, Andrea, Morelli, Gianluca and Riani, Marco (2015) Finding the number of disparate clusters with background contamination. In: Lausen, Berthold, Krolak-Schwerdt, Sabine and Böhmer, Matthias, (eds.) Data Science, Learning by Latent Structures, and Knowledge Discovery. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, pp. 29-42. ISBN 9783662449820

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Abstract

The Forward Search is used in an exploratory manner, with many random starts, to indicate the number of clusters and their membership in continuous data. The prospective clusters can readily be distinguished from background noise and from other forms of outliers. A confirmatory Forward Search, involving control on the sizes of statistical tests, establishes precise cluster membership. The method performs as well as robust methods such as TCLUST. However, it does not require prior specification of the number of clusters, nor of the level of trimming of outliers. In this way it is “user friendly”.

Item Type:	Book Section
Official URL:	http://www.springer.com/
Additional Information:	© 2015 Springer-Verlag Berlin Heidelberg
Library of Congress subject classification:	H Social Sciences > HA Statistics
Sets:	Departments > Statistics
Project and Funder Information:	Project ID Funder Name Funder ID MISURA Research Italy UNSPECIFIED
Date Deposited:	19 Sep 2016 12:28
URL:	http://eprints.lse.ac.uk/67782/

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