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: | (AM) Accepted Manuscript Download PDF (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 |
| Date accepted: | No date available |
| Date deposited: | 08 April 2009 |
| Date of first online publication: | January 2005 |
| Date first made open access: | No date available |
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