A nonlinear aggregation type classifier

Autores
Cholaquidis, Alejandro; Fraiman, Jacob Ricardo; Kalemkerian, Juan; Llop Orzan, Pamela Nerina
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We introduce a nonlinear aggregation type classifier for functional data defined on a separable and complete metric space. The new rule is built up from a collection of M arbitrary training classifiers. If the classifiers are consistent, then so is the aggregation rule. Moreover, asymptotically the aggregation rule behaves as well as the best of the M classifiers. The results of a small simulation are reported both, for high dimensional and functional data, and a real data example is analyzed.
Fil: Cholaquidis, Alejandro. Universidad de la República. Facultad de Ciencias; Uruguay
Fil: Fraiman, Jacob Ricardo. Universidad de la República. Facultad de Ciencias; Uruguay
Fil: Kalemkerian, Juan. Universidad de la República. Facultad de Ciencias; Uruguay
Fil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Materia
FUNCTIONAL DATA
NON-LINEAR AGGREGATION
SUPERVISED CLASSIFICATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/70989
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A nonlinear aggregation type classifierCholaquidis, AlejandroFraiman, Jacob RicardoKalemkerian, JuanLlop Orzan, Pamela NerinaFUNCTIONAL DATANON-LINEAR AGGREGATIONSUPERVISED CLASSIFICATIONhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We introduce a nonlinear aggregation type classifier for functional data defined on a separable and complete metric space. The new rule is built up from a collection of M arbitrary training classifiers. If the classifiers are consistent, then so is the aggregation rule. Moreover, asymptotically the aggregation rule behaves as well as the best of the M classifiers. The results of a small simulation are reported both, for high dimensional and functional data, and a real data example is analyzed.Fil: Cholaquidis, Alejandro. Universidad de la República. Facultad de Ciencias; UruguayFil: Fraiman, Jacob Ricardo. Universidad de la República. Facultad de Ciencias; UruguayFil: Kalemkerian, Juan. Universidad de la República. Facultad de Ciencias; UruguayFil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaElsevier Inc2016-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/70989Cholaquidis, Alejandro; Fraiman, Jacob Ricardo; Kalemkerian, Juan; Llop Orzan, Pamela Nerina; A nonlinear aggregation type classifier; Elsevier Inc; Journal Of Multivariate Analysis; 146; 4-2016; 269-2810047-259XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmva.2015.09.022info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0047259X15002365info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/abs/1509.01604info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:47:27Zoai:ri.conicet.gov.ar:11336/70989instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:47:27.514CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A nonlinear aggregation type classifier
title A nonlinear aggregation type classifier
spellingShingle A nonlinear aggregation type classifier
Cholaquidis, Alejandro
FUNCTIONAL DATA
NON-LINEAR AGGREGATION
SUPERVISED CLASSIFICATION
title_short A nonlinear aggregation type classifier
title_full A nonlinear aggregation type classifier
title_fullStr A nonlinear aggregation type classifier
title_full_unstemmed A nonlinear aggregation type classifier
title_sort A nonlinear aggregation type classifier
dc.creator.none.fl_str_mv Cholaquidis, Alejandro
Fraiman, Jacob Ricardo
Kalemkerian, Juan
Llop Orzan, Pamela Nerina
author Cholaquidis, Alejandro
author_facet Cholaquidis, Alejandro
Fraiman, Jacob Ricardo
Kalemkerian, Juan
Llop Orzan, Pamela Nerina
author_role author
author2 Fraiman, Jacob Ricardo
Kalemkerian, Juan
Llop Orzan, Pamela Nerina
author2_role author
author
author
dc.subject.none.fl_str_mv FUNCTIONAL DATA
NON-LINEAR AGGREGATION
SUPERVISED CLASSIFICATION
topic FUNCTIONAL DATA
NON-LINEAR AGGREGATION
SUPERVISED CLASSIFICATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We introduce a nonlinear aggregation type classifier for functional data defined on a separable and complete metric space. The new rule is built up from a collection of M arbitrary training classifiers. If the classifiers are consistent, then so is the aggregation rule. Moreover, asymptotically the aggregation rule behaves as well as the best of the M classifiers. The results of a small simulation are reported both, for high dimensional and functional data, and a real data example is analyzed.
Fil: Cholaquidis, Alejandro. Universidad de la República. Facultad de Ciencias; Uruguay
Fil: Fraiman, Jacob Ricardo. Universidad de la República. Facultad de Ciencias; Uruguay
Fil: Kalemkerian, Juan. Universidad de la República. Facultad de Ciencias; Uruguay
Fil: Llop Orzan, Pamela Nerina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
description We introduce a nonlinear aggregation type classifier for functional data defined on a separable and complete metric space. The new rule is built up from a collection of M arbitrary training classifiers. If the classifiers are consistent, then so is the aggregation rule. Moreover, asymptotically the aggregation rule behaves as well as the best of the M classifiers. The results of a small simulation are reported both, for high dimensional and functional data, and a real data example is analyzed.
publishDate 2016
dc.date.none.fl_str_mv 2016-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/70989
Cholaquidis, Alejandro; Fraiman, Jacob Ricardo; Kalemkerian, Juan; Llop Orzan, Pamela Nerina; A nonlinear aggregation type classifier; Elsevier Inc; Journal Of Multivariate Analysis; 146; 4-2016; 269-281
0047-259X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/70989
identifier_str_mv Cholaquidis, Alejandro; Fraiman, Jacob Ricardo; Kalemkerian, Juan; Llop Orzan, Pamela Nerina; A nonlinear aggregation type classifier; Elsevier Inc; Journal Of Multivariate Analysis; 146; 4-2016; 269-281
0047-259X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmva.2015.09.022
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0047259X15002365
info:eu-repo/semantics/altIdentifier/url/https://arxiv.org/abs/1509.01604
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Inc
publisher.none.fl_str_mv Elsevier Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613479071219712
score 13.070432

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