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Selecção de variáveis em estatística multivariada

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Resumo:The problem of variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. In this work we present and we discuss some new optimization criteria and others that are suggested by the literature. We present and we discuss the algorithms for the optimization problems resulting from the different criteria, as well as the calculated computational results. The criteria and algorithms are available in the package Subselect that is called from statistical program R. This package is in permanent update, with varied contributions, between which, this work is included. Package and program are of the public domain and meet available in the Internet. In this work we also discuss a multiple criteria optimization for the problem of identifying subsets of variables. In this approach, we are looking for subsets that are optimal for some criteria simultaneously. The induced total order for an only criterion gives place to a partial order, with which is associated a set of solutions that cannot simultaneously be improved in all the criteria. Usually they are called maximal, efficient solutions or Pareto optimal.
Autores principais:Minhoto, Manuel Joaquim Piteira
Assunto:variable selection multivariate statistics combinatorial optimization Heuristics Pareto optimal
Ano:2009
País:Portugal
Tipo de documento:tese de doutoramento
Tipo de acesso:acesso aberto
Instituição associada:Universidade de Lisboa
Idioma:português
Origem:Repositório da Universidade de Lisboa
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author Minhoto, Manuel Joaquim Piteira
author_facet Minhoto, Manuel Joaquim Piteira
author_role author
contributor_name_str_mv Cadima, Jorge Landerset
Cerdeira, Jorge Orestes
Repositório Científico de Acesso Aberto da ULisboa
country_str PT
creators_json_txt [{\"Person.name\":\"Minhoto, Manuel Joaquim Piteira\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Cadima, Jorge Landerset
Cerdeira, Jorge Orestes
Repositório Científico de Acesso Aberto da ULisboa
datacite.creators.creator.creatorName.fl_str_mv Minhoto, Manuel Joaquim Piteira
datacite.date.Accepted.fl_str_mv 2009-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2010-04-28T14:37:08Z
datacite.date.embargoed.fl_str_mv 2010-04-28T14:37:08Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv variable selection
multivariate statistics
combinatorial optimization
Heuristics
Pareto optimal
datacite.titles.title.fl_str_mv Selecção de variáveis em estatística multivariada
Variable selection in multivariate statistics
dc.contributor.none.fl_str_mv Cadima, Jorge Landerset
Cerdeira, Jorge Orestes
Repositório Científico de Acesso Aberto da ULisboa
dc.creator.none.fl_str_mv Minhoto, Manuel Joaquim Piteira
dc.date.Accepted.fl_str_mv 2009-01-01T00:00:00Z
dc.date.available.fl_str_mv 2010-04-28T14:37:08Z
dc.date.embargoed.fl_str_mv 2010-04-28T14:37:08Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10400.5/1877
dc.language.none.fl_str_mv por
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv variable selection
multivariate statistics
combinatorial optimization
Heuristics
Pareto optimal
dc.title.fl_str_mv Selecção de variáveis em estatística multivariada
Variable selection in multivariate statistics
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_db06
description The problem of variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. In this work we present and we discuss some new optimization criteria and others that are suggested by the literature. We present and we discuss the algorithms for the optimization problems resulting from the different criteria, as well as the calculated computational results. The criteria and algorithms are available in the package Subselect that is called from statistical program R. This package is in permanent update, with varied contributions, between which, this work is included. Package and program are of the public domain and meet available in the Internet. In this work we also discuss a multiple criteria optimization for the problem of identifying subsets of variables. In this approach, we are looking for subsets that are optimal for some criteria simultaneously. The induced total order for an only criterion gives place to a partial order, with which is associated a set of solutions that cannot simultaneously be improved in all the criteria. Usually they are called maximal, efficient solutions or Pareto optimal.
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person_str_mv Minhoto, Manuel Joaquim Piteira
publishDate 2009
reponame_str Repositório da Universidade de Lisboa
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spelling porptThe problem of variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. In this work we present and we discuss some new optimization criteria and others that are suggested by the literature. We present and we discuss the algorithms for the optimization problems resulting from the different criteria, as well as the calculated computational results. The criteria and algorithms are available in the package Subselect that is called from statistical program R. This package is in permanent update, with varied contributions, between which, this work is included. Package and program are of the public domain and meet available in the Internet. In this work we also discuss a multiple criteria optimization for the problem of identifying subsets of variables. In this approach, we are looking for subsets that are optimal for some criteria simultaneously. The induced total order for an only criterion gives place to a partial order, with which is associated a set of solutions that cannot simultaneously be improved in all the criteria. Usually they are called maximal, efficient solutions or Pareto optimal.application/pdfptSelecção de variáveis em estatística multivariadaAlternativeTitleptVariable selection in multivariate statisticsMinhoto, Manuel Joaquim PiteiraCadima, Jorge LandersetCerdeira, Jorge OrestesHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.pt2010-04-28T14:37:08Z20092009-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/1877http://purl.org/coar/access_right/c_abf2open accessvariable selectionmultivariate statisticscombinatorial optimizationHeuristicsPareto optimal1640585 bytesliteraturehttp://purl.org/coar/resource_type/c_db06doctoral thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/7a1ad239-d177-442a-b054-1e83f79a2662/download1213UTL - ISA, Lisboa
spellingShingle Selecção de variáveis em estatística multivariada
Minhoto, Manuel Joaquim Piteira
variable selection
multivariate statistics
combinatorial optimization
Heuristics
Pareto optimal
status SINGLETON
subject.fl_str_mv variable selection
multivariate statistics
combinatorial optimization
Heuristics
Pareto optimal
title Selecção de variáveis em estatística multivariada
title_full Selecção de variáveis em estatística multivariada
title_fullStr Selecção de variáveis em estatística multivariada
title_full_unstemmed Selecção de variáveis em estatística multivariada
title_short Selecção de variáveis em estatística multivariada
title_sort Selecção de variáveis em estatística multivariada
topic variable selection
multivariate statistics
combinatorial optimization
Heuristics
Pareto optimal
topic_facet variable selection
multivariate statistics
combinatorial optimization
Heuristics
Pareto optimal
url http://hdl.handle.net/10400.5/1877
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