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 / Heidelberg, Berlin, pp. 29-42. ISBN 9783662449820

PDF - Accepted Version Registered users only Download (21MB)

• Publisher
• Author

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
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	19 Sep 2016 12:28
Last Modified:	13 Sep 2024 17:30
Projects:	MISURA
Funders:	Research Italy
URI:	http://eprints.lse.ac.uk/id/eprint/67782

Actions (login required)

View Item