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Exploring multivariate data structures with local principal curves.

Einbeck, J. and Tutz, G. and Evers, L. (2005) 'Exploring multivariate data structures with local principal curves.', in Proceedings of the 28th Annual Conference of the Gesellschaft für Klassifikation, 9-11 March 2004, University of Dortmund. Heidelberg: Springer-Verlag, pp. 256-263. Studies in classification data analysis and knowledge organization. (28).

Abstract

A new approach to find the underlying structure of a multidimensional data cloud is proposed, which is based on a localized version of principal components analysis. More specifically, we calculate a series of local centers of mass and move through the data in directions given by the first local principal axis. One obtains a smooth ``local principal curve'' passing through the "middle" of a multivariate data cloud. The concept adopts to branched curves by considering the second local principal axis. Since the algorithm is based on a simple eigendecomposition, computation is fast and easy.

Item Type:Book chapter
Full text:PDF - Accepted Version (286Kb)
Status:Peer-reviewed
Publisher Web site:http://www.springer.com/computer/security+and+cryptology/book/978-3-540-25677-9
Publisher statement:The original publication is available at www.springerlink.com
Record Created:02 Feb 2009
Last Modified:28 Oct 2011 16:43

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