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dc.contributor.CRUESPUniversidade Estadual de Campinaspt_BR
dc.typeArtigo de periódicopt_BR
dc.titleComputational performance and cross-validation error precision of five PLS algorithms using designed and real data setspt_BR
dc.contributor.authorMartins, JPApt_BR
dc.contributor.authorTeofilo, RFpt_BR
dc.contributor.authorFerreira, MMCpt_BR
unicamp.author.emailmarcia@iqm.unicamp.brpt_BR
unicamp.authorMartins, Joao Paulo A. Teofilo, Reinaldo F. Ferreira, Marcia M. C. Univ Estadual Campinas, Inst Chem, Theoret & Appl Chemometr Lab, BR-13083970 Campinas, SP, Brazilpt_BR
unicamp.authorTeofilo, Reinaldo F. Univ Fed Vicosa, Instrumentat & Chemometr Lab, Dept Chem, BR-36571000 Vicosa, MG, Brazilpt_BR
dc.subjectcomputational performancept_BR
dc.subjectpartial least squarespt_BR
dc.subjectexperimental designpt_BR
dc.subjectalgorithmspt_BR
dc.subject.wosLeast-squares Regressionpt_BR
dc.subject.wosMultivariate Calibrationpt_BR
dc.subject.wosSpectroscopypt_BR
dc.subject.wosPredictionpt_BR
dc.subject.wosLanczospt_BR
dc.subject.wosClassificationpt_BR
dc.subject.wosProjectionpt_BR
dc.subject.wosTutorialpt_BR
dc.subject.wosToolpt_BR
dc.description.abstractAn evaluation of computational performance and precision regarding the cross-validation error of five partial least squares (PLS) algorithms (NIPALS, modified NIPALS, Kernel, SIMPLS and bidiagonal PLS), available and widely used in the literature, is presented. When dealing with large data sets, computational time is an important issue, mainly in cross-validation and variable selection. In the present paper, the PLS algorithms are compared in terms of the run time and the relative error in the precision obtained when performing leave-one-out cross-validation using simulated and real data sets. The simulated data sets were investigated through factorial and Latin square experimental designs. The evaluations were based on the number of rows, the number of columns and the number of latent variables. With respect to their performance, the results for both simulated and real data sets have shown that the differences in run time are statistically different. PIS bidiagonal is the fastest algorithm, followed by Kernel and SIMPLS. Regarding cross-validation error, all algorithms showed similar results. However, in some situations as, for example, when many latent variables were in question, discrepancies were observed, especially with respect to SIMPLS. Copyright (C) 2010 John Wiley & Sons, Ltd.pt
dc.relation.ispartofJournal Of Chemometricspt_BR
dc.relation.ispartofabbreviationJ. Chemometr.pt_BR
dc.publisher.cityChichesterpt_BR
dc.publisher.countryInglaterrapt_BR
dc.publisherJohn Wiley & Sons Ltdpt_BR
dc.date.issued2010pt_BR
dc.date.monthofcirculationMAY-JUNpt_BR
dc.identifier.citationJournal Of Chemometrics. John Wiley & Sons Ltd, v. 24, n. 41795, n. 320, n. 332, 2010.pt_BR
dc.language.isoenpt_BR
dc.description.volume24pt_BR
dc.description.issuenumber41795pt_BR
dc.description.firstpage320pt_BR
dc.description.lastpage332pt_BR
dc.rightsfechadopt_BR
dc.rights.licensehttp://olabout.wiley.com/WileyCDA/Section/id-406071.htmlpt_BR
dc.sourceWeb of Sciencept_BR
dc.identifier.issn0886-9383pt_BR
dc.identifier.wosidWOS:000280017700009pt_BR
dc.identifier.doi10.1002/cem.1309pt_BR
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.description.sponsorship1Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorship1Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.date.available2014-11-17T11:21:43Z
dc.date.available2015-11-26T16:42:29Z-
dc.date.accessioned2014-11-17T11:21:43Z
dc.date.accessioned2015-11-26T16:42:29Z-
dc.description.provenanceMade available in DSpace on 2014-11-17T11:21:43Z (GMT). No. of bitstreams: 1 WOS000280017700009.pdf: 523682 bytes, checksum: d00e2eaadede31957b3d21d9c992d944 (MD5) Previous issue date: 2010en
dc.description.provenanceMade available in DSpace on 2015-11-26T16:42:29Z (GMT). No. of bitstreams: 2 WOS000280017700009.pdf: 523682 bytes, checksum: d00e2eaadede31957b3d21d9c992d944 (MD5) WOS000280017700009.pdf.txt: 51027 bytes, checksum: bb3dd3db7d8136fb20814f4cec36489d (MD5) Previous issue date: 2010en
dc.identifier.urihttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/56415pt_BR
dc.identifier.urihttp://www.repositorio.unicamp.br/handle/REPOSIP/56415
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/56415-
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