Author
Listed:
- Colombe Becquart
(TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
- Aurore Archimbaud
(TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
- Anne Ruiz-Gazen
(TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
- Luka Prilé
(TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
- Klaus Nordhausen
(JYU - University of Jyväskylä)
Abstract
Invariant Coordinate Selection (ICS) is a multivariate technique that relies on the simultaneous diagonalization of two scatter matrices. It serves various purposes, including its use as a dimension reduction tool prior to clustering or outlier detection. Unlike methods such as Principal Component Analysis, ICS has a theoretical foundation that explains why and when the identified subspace should contain relevant information. These general results have been examined in detail primarily for specific scatter combinations within a two-cluster framework. In this study, we expand these investigations to include more clusters and scatter combinations. The case of three clusters in particular is studied at length. Based on these expanded theoretical insights and supported by numerical studies, we conclude that ICS is indeed suitable for recovering Fisher's discriminant subspace under very general settings and cases of failure seem rare.
Suggested Citation
Colombe Becquart & Aurore Archimbaud & Anne Ruiz-Gazen & Luka Prilé & Klaus Nordhausen, 2025.
"Invariant Coordinate Selection and Fisher Discriminant Subspace Beyond The Case of Two Groups,"
Working Papers
hal-05423125, HAL.
Handle:
RePEc:hal:wpaper:hal-05423125
Note: View the original document on HAL open archive server: https://hal.science/hal-05423125v1
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