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Autori principali: Becquart, Colombe, Archimbaud, Aurore, Ruiz-Gazen, Anne, Prilć, Luka, Nordhausen, Klaus
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2409.17631
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author Becquart, Colombe
Archimbaud, Aurore
Ruiz-Gazen, Anne
Prilć, Luka
Nordhausen, Klaus
author_facet Becquart, Colombe
Archimbaud, Aurore
Ruiz-Gazen, Anne
Prilć, Luka
Nordhausen, Klaus
contents 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. ICS's theoretical foundation establishes why and when the identified subspace should contain relevant information by demonstrating its connection with the Fisher discriminant subspace (FDS). 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. Our analysis reveals the importance of distinguishing whether the group centers matrix has full rank. In the full-rank case, we establish deeper connections between ICS and FDS. We provide a detailed study of these relationships for three clusters when the group centers matrix has full rank and when it does not. Based on these expanded theoretical insights and supported by numerical studies, we conclude that ICS is indeed suitable for recovering the FDS under very general settings and cases of failure seem rare.
format Preprint
id arxiv_https___arxiv_org_abs_2409_17631
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Invariant Coordinate Selection and Fisher discriminant subspace beyond the case of two groups
Becquart, Colombe
Archimbaud, Aurore
Ruiz-Gazen, Anne
Prilć, Luka
Nordhausen, Klaus
Methodology
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. ICS's theoretical foundation establishes why and when the identified subspace should contain relevant information by demonstrating its connection with the Fisher discriminant subspace (FDS). 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. Our analysis reveals the importance of distinguishing whether the group centers matrix has full rank. In the full-rank case, we establish deeper connections between ICS and FDS. We provide a detailed study of these relationships for three clusters when the group centers matrix has full rank and when it does not. Based on these expanded theoretical insights and supported by numerical studies, we conclude that ICS is indeed suitable for recovering the FDS under very general settings and cases of failure seem rare.
title Invariant Coordinate Selection and Fisher discriminant subspace beyond the case of two groups
topic Methodology
url https://arxiv.org/abs/2409.17631