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Exploring Multivariate Data Structures with Local Principal Curves

Einbeck, Jochen; Tutz, Gerhard; Evers, Ludger

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Authors

Gerhard Tutz

Ludger Evers



Contributors

C. Weihs
Editor

W. Gaul
Editor

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.

Citation

Einbeck, J., Tutz, G., & Evers, L. (2005). Exploring Multivariate Data Structures with Local Principal Curves. In C. Weihs, & W. Gaul (Eds.), Proceedings of the 28th Annual Conference of the Gesellschaft für Klassifikation, 9-11 March 2004, University of Dortmund (256-263)

Conference Name 28th Annual Conference of the German Classiciation Society.
Conference Location Magedeburg, Germany
Publication Date Jan 1, 2005
Deposit Date Feb 2, 2009
Publicly Available Date Apr 8, 2009
Publisher Springer Verlag
Pages 256-263
Series Title Studies in classification data analysis and knowledge organization
Series Number 28
Book Title Proceedings of the 28th Annual Conference of the Gesellschaft für Klassifikation, 9-11 March 2004, University of Dortmund.
Public URL https://durham-repository.worktribe.com/output/1162294
Publisher URL http://www.springer.com/computer/security+and+cryptology/book/978-3-540-25677-9

Files

Accepted Conference Proceeding (293 Kb)
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Copyright Statement
The original publication is available at www.springerlink.com







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