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Probabilistic clustering of interval data

2015Journal article Open access
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dc.contributor.authorBrito, Paula
dc.contributor.authorSilva, A. Pedro Duarte
dc.contributor.authorDias, José G.
dc.date.accessioned2016-06-28T11:36:48Z
dc.date.available2016-06-28T11:36:48Z
dc.date.issued2015
dc.description.abstractIn this paper we address the problem of clustering interval data, adopting a model-based approach. To this purpose, parametric models for interval-valued variables are used which consider configurations for the variance-covariance matrix that take the nature of the interval data directly into account. Results, both on synthetic and empirical data, clearly show the well-founding of the proposed approach. The method succeeds in finding parsimonious heterocedastic models which is a critical feature in many applications. Furthermore, the analysis of the different data sets made clear the need to explicitly consider the intrinsic variability present in interval data.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.citationBRITO, Paula; DUARTE SILVA, A. P.; DIAS, José G. - Probabilistic Clustering of Interval Data. Intelligent Data Analysis. 1571-4128. Vol. 19, n.º 2 (2015), p. 293-313pt_PT
dc.identifier.doi10.3233/IDA-150718
dc.identifier.eid84928572252
dc.identifier.eissn1088-467X
dc.identifier.issn1571-4128
dc.identifier.urihttp://hdl.handle.net/10400.14/20309
dc.identifier.wos000353062400006
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIOS Press
dc.relationNORTE-07-0124-FEDER-000059
dc.relationStrategic Project - UI 731 - 2011-2012
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectClustering methodspt_PT
dc.subjectFinite mixture modelspt_PT
dc.subjectInterval-valued variablept_PT
dc.subjectIntrinsic variabilitypt_PT
dc.subjectSymbolic datapt_PT
dc.titleProbabilistic clustering of interval datapt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleStrategic Project - UI 731 - 2011-2012
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/PEst-OE%2FEGE%2FUI0731%2F2011/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEGE-GES%2F103223%2F2008/PT
oaire.citation.endPage313
oaire.citation.issue2
oaire.citation.startPage293
oaire.citation.titleIntelligent Data Analysis
oaire.citation.volume19
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream3599-PPCDT
person.familyNameBrito
person.familyNameDuarte Silva
person.givenNamePaula
person.givenNamePedro
person.identifierR-000-CF4
person.identifier.ciencia-id0B1A-DD19-07CE
person.identifier.ciencia-id371F-636A-E2E9
person.identifier.orcid0000-0002-2593-8818
person.identifier.orcid0000-0003-1378-2403
person.identifier.ridJ-6656-2013
person.identifier.ridB-6168-2008
person.identifier.scopus-author-id15025681300
person.identifier.scopus-author-id6602627961
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication3cd7537f-4e5a-4953-9775-1d78a6d6500b
relation.isAuthorOfPublication2a796b4b-6325-4af6-a47e-d233ccde3b53
relation.isAuthorOfPublication.latestForDiscovery2a796b4b-6325-4af6-a47e-d233ccde3b53
relation.isProjectOfPublicationd1ff3892-c183-4fec-a8ad-4e25cbc6ebe6
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