Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications

Autores
Azcarate, Silvana Mariela; de Araújo Gomes, Adriano; Muñoz de la Peña, Arsenio; Goicoechea, Hector Casimiro
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This review outlines some of the challenging aspects of applying second-order data modeling in classification issues analyzing selected examples of current applications. The main analytical platforms used for classification are briefly discussed from the application point of view, and the utilization of the generated data is illustrated. After a critical discussion of the advantages concerning the general features of the available algorithms and their underlying models, one example is presented and discussed in detail with the purpose of illustrating the high potentiality of second-order data modeling in the classification field. In addition, advanced data pre-processing tools, prior to multivariate analysis, are explained, and relevant tools are displayed. Finally, novelty prospects in multi-way classification area are presented.
Fil: Azcarate, Silvana Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa; Argentina
Fil: de Araújo Gomes, Adriano. Universidade Federal do Rio Grande do Sul; Brasil
Fil: Muñoz de la Peña, Arsenio. Universidad de Extremadura; España
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Materia
CHROMATOGRAPHY
CLASSIFICATION
EXCITATION-EMISSION FLUORESCENCE MATRIX
SECOND-ORDER DATA MODELING
THREE-WAY
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:11336/83077
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/83077
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applicationsAzcarate, Silvana Marielade Araújo Gomes, AdrianoMuñoz de la Peña, ArsenioGoicoechea, Hector CasimiroCHROMATOGRAPHYCLASSIFICATIONEXCITATION-EMISSION FLUORESCENCE MATRIXSECOND-ORDER DATA MODELINGTHREE-WAYhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1This review outlines some of the challenging aspects of applying second-order data modeling in classification issues analyzing selected examples of current applications. The main analytical platforms used for classification are briefly discussed from the application point of view, and the utilization of the generated data is illustrated. After a critical discussion of the advantages concerning the general features of the available algorithms and their underlying models, one example is presented and discussed in detail with the purpose of illustrating the high potentiality of second-order data modeling in the classification field. In addition, advanced data pre-processing tools, prior to multivariate analysis, are explained, and relevant tools are displayed. Finally, novelty prospects in multi-way classification area are presented.Fil: Azcarate, Silvana Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa; ArgentinaFil: de Araújo Gomes, Adriano. Universidade Federal do Rio Grande do Sul; BrasilFil: Muñoz de la Peña, Arsenio. Universidad de Extremadura; EspañaFil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaElsevier2018-10info: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/11336/83077Azcarate, Silvana Mariela; de Araújo Gomes, Adriano; Muñoz de la Peña, Arsenio; Goicoechea, Hector Casimiro; Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications; Elsevier; Trac-Trends In Analytical Chemistry; 107; 10-2018; 151-1680165-9936CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0165993618302322info:eu-repo/semantics/altIdentifier/doi/10.1016/j.trac.2018.07.022info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:38:59Zoai:ri.conicet.gov.ar:11336/83077instacron: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 09:38:59.697CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
title Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
spellingShingle Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
Azcarate, Silvana Mariela
CHROMATOGRAPHY
CLASSIFICATION
EXCITATION-EMISSION FLUORESCENCE MATRIX
SECOND-ORDER DATA MODELING
THREE-WAY
title_short Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
title_full Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
title_fullStr Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
title_full_unstemmed Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
title_sort Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications
dc.creator.none.fl_str_mv Azcarate, Silvana Mariela
de Araújo Gomes, Adriano
Muñoz de la Peña, Arsenio
Goicoechea, Hector Casimiro
author Azcarate, Silvana Mariela
author_facet Azcarate, Silvana Mariela
de Araújo Gomes, Adriano
Muñoz de la Peña, Arsenio
Goicoechea, Hector Casimiro
author_role author
author2 de Araújo Gomes, Adriano
Muñoz de la Peña, Arsenio
Goicoechea, Hector Casimiro
author2_role author
author
author
dc.subject.none.fl_str_mv CHROMATOGRAPHY
CLASSIFICATION
EXCITATION-EMISSION FLUORESCENCE MATRIX
SECOND-ORDER DATA MODELING
THREE-WAY
topic CHROMATOGRAPHY
CLASSIFICATION
EXCITATION-EMISSION FLUORESCENCE MATRIX
SECOND-ORDER DATA MODELING
THREE-WAY
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv This review outlines some of the challenging aspects of applying second-order data modeling in classification issues analyzing selected examples of current applications. The main analytical platforms used for classification are briefly discussed from the application point of view, and the utilization of the generated data is illustrated. After a critical discussion of the advantages concerning the general features of the available algorithms and their underlying models, one example is presented and discussed in detail with the purpose of illustrating the high potentiality of second-order data modeling in the classification field. In addition, advanced data pre-processing tools, prior to multivariate analysis, are explained, and relevant tools are displayed. Finally, novelty prospects in multi-way classification area are presented.
Fil: Azcarate, Silvana Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa; Argentina
Fil: de Araújo Gomes, Adriano. Universidade Federal do Rio Grande do Sul; Brasil
Fil: Muñoz de la Peña, Arsenio. Universidad de Extremadura; España
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
description This review outlines some of the challenging aspects of applying second-order data modeling in classification issues analyzing selected examples of current applications. The main analytical platforms used for classification are briefly discussed from the application point of view, and the utilization of the generated data is illustrated. After a critical discussion of the advantages concerning the general features of the available algorithms and their underlying models, one example is presented and discussed in detail with the purpose of illustrating the high potentiality of second-order data modeling in the classification field. In addition, advanced data pre-processing tools, prior to multivariate analysis, are explained, and relevant tools are displayed. Finally, novelty prospects in multi-way classification area are presented.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
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/11336/83077
Azcarate, Silvana Mariela; de Araújo Gomes, Adriano; Muñoz de la Peña, Arsenio; Goicoechea, Hector Casimiro; Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications; Elsevier; Trac-Trends In Analytical Chemistry; 107; 10-2018; 151-168
0165-9936
CONICET Digital
CONICET
url http://hdl.handle.net/11336/83077
identifier_str_mv Azcarate, Silvana Mariela; de Araújo Gomes, Adriano; Muñoz de la Peña, Arsenio; Goicoechea, Hector Casimiro; Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications; Elsevier; Trac-Trends In Analytical Chemistry; 107; 10-2018; 151-168
0165-9936
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0165993618302322
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.trac.2018.07.022
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
publisher.none.fl_str_mv Elsevier
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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score 13.070432

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