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acessibilidade

http://hdl.handle.net/10071/13944
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acessibilidade
DC FieldValueLanguage
dc.contributor.authorMartins, M. C.-
dc.contributor.authorCardoso, M. G. M. S.-
dc.date.accessioned2017-07-11T15:09:23Z-
dc.date.available2017-07-11T15:09:23Z-
dc.date.issued2008-
dc.identifier.issn2182-1801-
dc.identifier.urihttps://ciencia.iscte-iul.pt/id/ci-pub-10480-
dc.identifier.urihttp://hdl.handle.net/10071/13944-
dc.description.abstractThis work is focused on the evaluation of a clustering of credit card holders of a Portuguese financial organization, using a cross-validation procedure which is imported from supervised learning and used for evaluating results yielded by cluster analysis (an unsupervised technique). The proposed approach is conceived to deal with the particular sample characteristics – it handles a large data set and mixed (numerical and categorical) variables. This approach provides both the evaluation of the clustering solution and helps characterizing the clusters. Furthermore, it provides classification rules for new credit card holders. According to the obtained results, the internal stability is verified for a solution with five clusters. Finally, this work presents the profiles of the credit card holders’ clusters and suggests some possible strategies to study in each of them, in the business context.por
dc.language.isoengpor
dc.publisherUniversidade Abertapor
dc.rightsopenAccesspor
dc.subjectClusteringpor
dc.subjectClustering evaluationpor
dc.subjectInternal stabilitypor
dc.titleEvaluation of clusters of credit cards holderspor
dc.typearticlepor
dc.pagination1-11en_US
dc.peerreviewedyespor
dc.journalRevista de Ciências da Computaçãoen_US
dc.volume3en_US
dc.number3en_US
degois.publication.firstPage1por
degois.publication.lastPage11por
degois.publication.issue3por
degois.publication.titleRevista de Ciências da Computaçãopor
dc.date.updated2017-07-11T15:08:52Z-
Appears in Collections:DMQGE-RN - Artigos em revistas nacionais com arbitragem científica

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