Eigenvalue based spectral classification

This paper describes a new method of classification based on spectral analysis. The motivations behind developing the new model were the failures of the classical spectral cluster analysis based on combinatorial and normalized Laplacian for a set of real-world datasets of textual documents. Reasons...

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Detalles Bibliográficos
Autores principales: Borkowski, Piotr, Kłopotek, Mieczysław A., Starosta, Bartłomiej, Wierzchoń, Sławomir T., Sydow, Marcin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079090/
https://www.ncbi.nlm.nih.gov/pubmed/37023089
http://dx.doi.org/10.1371/journal.pone.0283413
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author Borkowski, Piotr
Kłopotek, Mieczysław A.
Starosta, Bartłomiej
Wierzchoń, Sławomir T.
Sydow, Marcin
author_facet Borkowski, Piotr
Kłopotek, Mieczysław A.
Starosta, Bartłomiej
Wierzchoń, Sławomir T.
Sydow, Marcin
author_sort Borkowski, Piotr
collection PubMed
description This paper describes a new method of classification based on spectral analysis. The motivations behind developing the new model were the failures of the classical spectral cluster analysis based on combinatorial and normalized Laplacian for a set of real-world datasets of textual documents. Reasons of the failures are analysed. While the known methods are all based on usage of eigenvectors of graph Laplacians, a new classification method based on eigenvalues of graph Laplacians is proposed and studied.
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spelling pubmed-100790902023-04-07 Eigenvalue based spectral classification Borkowski, Piotr Kłopotek, Mieczysław A. Starosta, Bartłomiej Wierzchoń, Sławomir T. Sydow, Marcin PLoS One Research Article This paper describes a new method of classification based on spectral analysis. The motivations behind developing the new model were the failures of the classical spectral cluster analysis based on combinatorial and normalized Laplacian for a set of real-world datasets of textual documents. Reasons of the failures are analysed. While the known methods are all based on usage of eigenvectors of graph Laplacians, a new classification method based on eigenvalues of graph Laplacians is proposed and studied. Public Library of Science 2023-04-06 /pmc/articles/PMC10079090/ /pubmed/37023089 http://dx.doi.org/10.1371/journal.pone.0283413 Text en © 2023 Borkowski et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Borkowski, Piotr
Kłopotek, Mieczysław A.
Starosta, Bartłomiej
Wierzchoń, Sławomir T.
Sydow, Marcin
Eigenvalue based spectral classification
title Eigenvalue based spectral classification
title_full Eigenvalue based spectral classification
title_fullStr Eigenvalue based spectral classification
title_full_unstemmed Eigenvalue based spectral classification
title_short Eigenvalue based spectral classification
title_sort eigenvalue based spectral classification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079090/
https://www.ncbi.nlm.nih.gov/pubmed/37023089
http://dx.doi.org/10.1371/journal.pone.0283413
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AT sydowmarcin eigenvaluebasedspectralclassification

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