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Enhancing the selection of a model-based clustering with external categorical variables

dc.contributor.authorBaudry, Jean-Patrick
dc.contributor.authorCardoso, Margarida
dc.contributor.authorCeleux, Gilles
dc.contributor.authorAmorim, Maria José de Pina da Cruz
dc.contributor.authorFerreira, Ana Sousa
dc.date.accessioned2016-04-14T14:45:58Z
dc.date.available2016-04-14T14:45:58Z
dc.date.issued2015-06
dc.description.abstractIn cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion.pt_PT
dc.identifier.citationBAUDRY, JEAN-PATRICK; [et al.] - Enhancing the selection of a model-based clustering with external categorical variables. Advances in Data Analysis and Classification. ISSN.1862-5347. Vol. 9, N.º 2 (2015), pp. 177-196.pt_PT
dc.identifier.doi10.1007/s11634-014-0177-3pt_PT
dc.identifier.issn1862-5347
dc.identifier.issn1862-5355
dc.identifier.urihttp://hdl.handle.net/10400.21/5977
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Heidelbergpt_PT
dc.relation.publisherversionhttp://link.springer.com/article/10.1007/s11634-014-0177-3pt_PT
dc.subjectMixture modelspt_PT
dc.subjectModel-based clusteringpt_PT
dc.subjectNumber of clusterspt_PT
dc.subjectPenalised criteriapt_PT
dc.subjectCategorical variablespt_PT
dc.subjectBICpt_PT
dc.subjectICLpt_PT
dc.subjectMixed type variables clusteringpt_PT
dc.titleEnhancing the selection of a model-based clustering with external categorical variablespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage196pt_PT
oaire.citation.issue2pt_PT
oaire.citation.startPage177pt_PT
oaire.citation.volume9pt_PT
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT

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