Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/2514
Full metadata record
DC FieldValueLanguage
dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.typeArtigo de periódicopt_BR
dc.titleSemi-Supervised Dimensionality Reduction based on Partial Least Squares for Visual Analysis of High Dimensional Datapt_BR
dc.contributor.authorPaiva, Jose Gustavo S.pt_BR
dc.contributor.authorSchwartz, William Robsonpt_BR
dc.contributor.authorPedrini, Heliopt_BR
dc.contributor.authorMinghim, Rosanept_BR
unicamp.authorSchwartz, William Robsonpt_BR
unicamp.authorPedrini, Heliopt_BR
unicamp.author.externalPaiva, Jose Gustavo S.pt
unicamp.author.externalMinghim, Rosanept
dc.subject.wosMULTIDIMENSIONAL PROJECTIONpt_BR
dc.subject.wosVARIABLE SELECTIONpt_BR
dc.subject.wosREGRESSIONpt_BR
dc.subject.wosCLASSIFICATIONpt_BR
dc.subject.wosSIMILARITYpt_BR
dc.description.abstractDimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.pt
dc.relation.ispartofComputer Graphics Forumpt_BR
dc.publisher.cityHobokenpt_BR
dc.publisherWiley-Blackwellpt_BR
dc.date.issued2012pt_BR
dc.identifier.citationComputer Graphics Forum. Wiley-Blackwell, v.31, n.3, p.1345-1354, 2012pt_BR
dc.language.isoengpt_BR
dc.description.volume31pt_BR
dc.description.issuenumber3pt_BR
dc.description.firstpage1345pt_BR
dc.description.lastpage1354pt_BR
dc.rightsfechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn0167-7055pt_BR
dc.identifier.wosidWOS:000305604000010pt_BR
dc.identifier.doi10.1111/j.1467-8659.2012.03126.xpt_BR
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorshipBrazilian financial agency FAPESPpt_BR
dc.description.sponsorship1Fundação 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.date.available2013-09-19T18:06:56Z
dc.date.available2016-06-30T18:10:29Z-
dc.date.accessioned2013-09-19T18:06:56Z
dc.date.accessioned2016-06-30T18:10:29Z-
dc.description.provenanceMade available in DSpace on 2013-09-19T18:06:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2012en
dc.description.provenanceMade available in DSpace on 2016-06-30T18:10:29Z (GMT). No. of bitstreams: 0 Previous issue date: 2012en
dc.identifier.urihttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/2514
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/2514-
dc.contributor.departmentTeoria da Computação
dc.contributor.unidadeICpt
Appears in Collections:IC - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.