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).
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)|
|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|
|Social bookmarking:||Export: EndNote, Zotero | BibTex|
|Usage statistics||Look up in GoogleScholar | Find in a UK Library|