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A feature selection algorithm based on heuristic decomposition

2017Journal article Open access
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dc.contributor.authorCavique, Luís
dc.contributor.authorMendes, Armando B.
dc.contributor.authorMartiniano, Hugo F. M. C.
dc.date.accessioned2018-11-06T12:36:45Z
dc.date.available2018-11-06T12:36:45Z
dc.date.issued2017
dc.description.abstractFeature selection is one of the most important concepts in data mining when dimensionality reduction is needed. The performance measures of feature selection encompass predictive accuracy and result comprehensibility. Consistency based feature selection is a significant category of feature selection research that substantially improves the comprehensibility of the result using the parsimony principle. In this work, the feature selection algorithm LAID, Logical Analysis of Inconsistent Data, is applied to large volumes of data. In order to deal with hundreds of thousands of attributes, a problem de-composition strategy associated with a set covering problem formulation is used. The algorithm is applied to artificial datasets with genome-like characteristics of patients with rare diseases.pt_PT
dc.description.sponsorshipThe first author would like to thank the FCT support UID/Multi/04046/2013. This work used the EGI infrastructure with the support of NCG-INGRID-PT (Portugal) and BIFI (Spain).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/978-3-319-65340-2_43pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.2/7645
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-319-65340-2_43#citeaspt_PT
dc.subjectData miningpt_PT
dc.subjectFeature selectionpt_PT
dc.subjectConsistency measurept_PT
dc.subjectSet covering problempt_PT
dc.subjectHeuristic decompositionpt_PT
dc.titleA feature selection algorithm based on heuristic decompositionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FMulti%2F04046%2F2013/PT
oaire.citation.endPage536pt_PT
oaire.citation.startPage525pt_PT
oaire.citation.titleProgress in Artificial Intelligencept_PT
oaire.fundingStream5876
person.familyNameCavique
person.familyNameB Mendes
person.familyNameMartiniano
person.givenNameLuís
person.givenNameArmando
person.givenNameHugo Filipe de Mesquita Costa
person.identifier1008054
person.identifier.ciencia-id911E-84AC-3956
person.identifier.ciencia-idEE1E-90E7-2751
person.identifier.ciencia-id1E13-00FA-3C8B
person.identifier.orcid0000-0002-5590-1493
person.identifier.orcid0000-0003-3049-5852
person.identifier.orcid0000-0003-2490-8913
person.identifier.ridN-7280-2015
person.identifier.ridR-7571-2017
person.identifier.scopus-author-id13003839500
person.identifier.scopus-author-id16743962700
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication40906a16-46a2-42f1-b26d-7db7012294ee
relation.isAuthorOfPublicationd26eb57f-648e-485c-bd92-efcc8cb1b3be
relation.isAuthorOfPublication64ea6a03-f22d-4a28-9391-46a785f6790f
relation.isAuthorOfPublication.latestForDiscoveryd26eb57f-648e-485c-bd92-efcc8cb1b3be
relation.isProjectOfPublicationab8b249f-48e9-42c8-8786-c1976e895516
relation.isProjectOfPublication.latestForDiscoveryab8b249f-48e9-42c8-8786-c1976e895516

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