Feature selection for functional data
- Autores
- Fraiman, Ricardo; Gimenez, Yanina; Svarc, Marcela
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- We herein introduce a general procedure to capture the relevant information from a functional data set in relation to a statistical method used to analyze the data, such as, classification, regression or principal components. The aim is to identify a small subset of functions that can "better explain" the model, highlighting its most important features. We obtain consistency results for our proposals. The computational aspects are analyzed, a heuristic stochastic algorithm is introduced and real data sets are studied.
Fil: Fraiman, Ricardo. Universidad de la República; Uruguay
Fil: Gimenez, Yanina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina
Fil: Svarc, Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina - Materia
-
CLASSIFICATION
PRINCIPAL COMPONENTS
REGRESSION
VARIABLE SELECTION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/90813
Ver los metadatos del registro completo
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Feature selection for functional dataFraiman, RicardoGimenez, YaninaSvarc, MarcelaCLASSIFICATIONPRINCIPAL COMPONENTSREGRESSIONVARIABLE SELECTIONhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We herein introduce a general procedure to capture the relevant information from a functional data set in relation to a statistical method used to analyze the data, such as, classification, regression or principal components. The aim is to identify a small subset of functions that can "better explain" the model, highlighting its most important features. We obtain consistency results for our proposals. The computational aspects are analyzed, a heuristic stochastic algorithm is introduced and real data sets are studied.Fil: Fraiman, Ricardo. Universidad de la República; UruguayFil: Gimenez, Yanina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; ArgentinaFil: Svarc, Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; ArgentinaElsevier Inc2016-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/zipapplication/pdfhttp://hdl.handle.net/11336/90813Fraiman, Ricardo; Gimenez, Yanina; Svarc, Marcela; Feature selection for functional data; Elsevier Inc; Journal Of Multivariate Analysis; 146; 4-2016; 191-2080047-259XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0047259X15002201info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmva.2015.09.006info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:42:04Zoai:ri.conicet.gov.ar:11336/90813instacron: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 09:42:04.528CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Feature selection for functional data |
title |
Feature selection for functional data |
spellingShingle |
Feature selection for functional data Fraiman, Ricardo CLASSIFICATION PRINCIPAL COMPONENTS REGRESSION VARIABLE SELECTION |
title_short |
Feature selection for functional data |
title_full |
Feature selection for functional data |
title_fullStr |
Feature selection for functional data |
title_full_unstemmed |
Feature selection for functional data |
title_sort |
Feature selection for functional data |
dc.creator.none.fl_str_mv |
Fraiman, Ricardo Gimenez, Yanina Svarc, Marcela |
author |
Fraiman, Ricardo |
author_facet |
Fraiman, Ricardo Gimenez, Yanina Svarc, Marcela |
author_role |
author |
author2 |
Gimenez, Yanina Svarc, Marcela |
author2_role |
author author |
dc.subject.none.fl_str_mv |
CLASSIFICATION PRINCIPAL COMPONENTS REGRESSION VARIABLE SELECTION |
topic |
CLASSIFICATION PRINCIPAL COMPONENTS REGRESSION VARIABLE SELECTION |
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 herein introduce a general procedure to capture the relevant information from a functional data set in relation to a statistical method used to analyze the data, such as, classification, regression or principal components. The aim is to identify a small subset of functions that can "better explain" the model, highlighting its most important features. We obtain consistency results for our proposals. The computational aspects are analyzed, a heuristic stochastic algorithm is introduced and real data sets are studied. Fil: Fraiman, Ricardo. Universidad de la República; Uruguay Fil: Gimenez, Yanina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina Fil: Svarc, Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina |
description |
We herein introduce a general procedure to capture the relevant information from a functional data set in relation to a statistical method used to analyze the data, such as, classification, regression or principal components. The aim is to identify a small subset of functions that can "better explain" the model, highlighting its most important features. We obtain consistency results for our proposals. The computational aspects are analyzed, a heuristic stochastic algorithm is introduced and real data sets are studied. |
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/11336/90813 Fraiman, Ricardo; Gimenez, Yanina; Svarc, Marcela; Feature selection for functional data; Elsevier Inc; Journal Of Multivariate Analysis; 146; 4-2016; 191-208 0047-259X CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/90813 |
identifier_str_mv |
Fraiman, Ricardo; Gimenez, Yanina; Svarc, Marcela; Feature selection for functional data; Elsevier Inc; Journal Of Multivariate Analysis; 146; 4-2016; 191-208 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/url/http://www.sciencedirect.com/science/article/pii/S0047259X15002201 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jmva.2015.09.006 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/zip 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 |
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1844613326437351424 |
score |
13.070432 |