Exploring Multivariate Data Structures with Local Principal Curves

Einbeck, Jochen; Tutz, Gerhard; Evers, Ludger

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, January). Exploring Multivariate Data Structures with Local Principal Curves. Presented at 28th Annual Conference of the German Classiciation Society., Magedeburg, Germany

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 28th Annual Conference of the German Classiciation Society.
• 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