Abstract
In the medical sciences as well as in other contexts we often have to deal with the study of groups and with the research of their separation. The aim of this paper is to highlight how, in some situations, Partial Least Squares (PLS) Discriminant Analysis (Sjöström et al., 1986) can lead to a solution that is not an answer to the given problem of discrimination. Within a PLS framework, the authors provide two extensions of it. The first is close to the Generalized PLS proposed by (1997) but used in the discrimination context. The second proposal, in the same framework, leads to consider the PLS Redundancy Analysis proposed by (1995) by using suitable metrics. Some examples of data treatment are given.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
CAZES, P. (1997): Adaptation de la régression PLS au cas de la régression aprés analyse des correspondances multiples. Revue de Statistique Appliquées, XLV(2), 89–99
CHESSEL, D., DOLEDEC, S. (1993): ADE Version 3.6: HypercardStack and Program library for the Analysis of Environment Data. User’s Manual
ESPOSITO VINCI, V., TENENHAUS, M. (2001): PLS Logistic Regression. In V. Esposito Vinci, C. Lauro, A. Morineau and M. Tenenhaus (Eds.): Pls and related methods. Cisia 89–99.
PERSAT, H., (1978): Ecologie de l’Ombre commun. Bulletin de la Revue Francaise de Pisciculture, 26, 11–20.
SAPORTA, G. (1990): Probabilité, analyse des données et statistique. Editions Technip, Paris, 493p.
SJÖSTRÖM, M., WOLD S. and SÖDERSTRÖM, B. (1986): PLS Discrimination plots. In E.S. Gelsema and L.N. Kanals (Eds.): Pattern Recognition in Practice II. Elsevier, Amsterdam
TENENHAUS, M. (1995): A partial least squares approach to multiple regression, redundancy analysis and canonical analysis. Les Cahiers de Recherche de HEC, CR 550/1995.
TENENHAUS, M. (1998): La Régression PLS. Théorie et pratique. Editions Technip, Paris, 254p.
TOMASSONE, R., DANZART, M., DAUDIN, J.J. and MASSON, J.P. (1988): Discrimination et classement. Masson, Paris, 172p.
WOLD, H. (1966): Estimation of principal components and related models by iterative least squares. In P.R. Krishnaiah (Eds.) Multivariate Analysis. Academic Press, New York.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sabatier, R., Vivien, M., Amenta, P. (2003). Two Approaches for Discriminant Partial Least Squares. In: Schader, M., Gaul, W., Vichi, M. (eds) Between Data Science and Applied Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18991-3_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-18991-3_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40354-8
Online ISBN: 978-3-642-18991-3
eBook Packages: Springer Book Archive