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Two Approaches for Discriminant Partial Least Squares

  • Robert Sabatier
  • Myrtille Vivien
  • Pietro Amenta
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

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.

Keywords

Partial Little Square Partial Little Square Regression Statistical Unit Partial Little Square Model Partial Little Square Discriminant Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Robert Sabatier
    • 1
  • Myrtille Vivien
    • 1
  • Pietro Amenta
    • 2
  1. 1.Laboratoire de Physique Moléculaire et Structurale, UMR 5094Faculté de PharmacieMontpellier Cedex 5France
  2. 2.Department of Economics, Mathematic and StatisticsUniversity of LecceLecceItaly

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