On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection

This is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Change...

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Detalles Bibliográficos
Autores: Rodríguez-Luján, Irene, Santa Cruz Fernández, Carlos, Huerta, Ramón
Tipo de recurso: artículo
Fecha de publicación:2011
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/667689
Acceso en línea:http://hdl.handle.net/10486/667689
https://dx.doi.org/10.1016/j.patrec.2011.04.007
Access Level:acceso abierto
Palabra clave:Feature selection
Kernel Fisher discriminant
Kernel methods
Quadratic Programming Feature Selection
Informática
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spelling On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature SelectionRodríguez-Luján, IreneSanta Cruz Fernández, CarlosHuerta, RamónFeature selectionKernel Fisher discriminantKernel methodsQuadratic Programming Feature SelectionInformáticaThis is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Letters, Vol. 32, Iss. 11, (2011) DOI: 10.1016/j.patrec.2011.04.007We reformulate the Quadratic Programming Feature Selection (QPFS) method in a Kernel space to obtain a vector which maximizes the quadratic objective function of QPFS. We demonstrate that the vector obtained by Kernel Quadratic Programming Feature Selection is equivalent to the Kernel Fisher vector and, therefore, a new interpretation of the Kernel Fisher discriminant analysis is given which provides some computational advantages for highly unbalanced datasets.I.R.-L. is supported by an FPU grant from Universidad Autónoma de Madrid, and partially supported by the Universidad Autónoma de Madrid-IIC Chair and TIN 2010-21575-C02-01. RH was partially supported by Grants ONRN00014-07-1-0741, and US Army Medical and Material Command under contract #W81XWH-10-C-0040 in collaboration with Elintrix, Inc.Elsevier B.V.Departamento de Ingeniería InformáticaEscuela Politécnica Superior20112011-08-01research articlehttp://purl.org/coar/resource_type/c_2df8fbb1AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/667689https://dx.doi.org/10.1016/j.patrec.2011.04.007reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/6676892026-06-23T12:46:27Z
dc.title.none.fl_str_mv On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
title On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
spellingShingle On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
Rodríguez-Luján, Irene
Feature selection
Kernel Fisher discriminant
Kernel methods
Quadratic Programming Feature Selection
Informática
title_short On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
title_full On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
title_fullStr On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
title_full_unstemmed On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
title_sort On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection
dc.creator.none.fl_str_mv Rodríguez-Luján, Irene
Santa Cruz Fernández, Carlos
Huerta, Ramón
author Rodríguez-Luján, Irene
author_facet Rodríguez-Luján, Irene
Santa Cruz Fernández, Carlos
Huerta, Ramón
author_role author
author2 Santa Cruz Fernández, Carlos
Huerta, Ramón
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería Informática
Escuela Politécnica Superior
dc.subject.none.fl_str_mv Feature selection
Kernel Fisher discriminant
Kernel methods
Quadratic Programming Feature Selection
Informática
topic Feature selection
Kernel Fisher discriminant
Kernel methods
Quadratic Programming Feature Selection
Informática
description This is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Letters, Vol. 32, Iss. 11, (2011) DOI: 10.1016/j.patrec.2011.04.007
publishDate 2011
dc.date.none.fl_str_mv 2011
2011-08-01
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10486/667689
https://dx.doi.org/10.1016/j.patrec.2011.04.007
url http://hdl.handle.net/10486/667689
https://dx.doi.org/10.1016/j.patrec.2011.04.007
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv reponame:Biblos-e Archivo. Repositorio Institucional de la UAM
instname:Universidad Autónoma de Madrid
instname_str Universidad Autónoma de Madrid
reponame_str Biblos-e Archivo. Repositorio Institucional de la UAM
collection Biblos-e Archivo. Repositorio Institucional de la UAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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