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Combining models in discrete discriminant analysis in the multiclass case

dc.contributor.authorMarques, Anabela
dc.contributor.authorFerreira, Ana Sousa
dc.contributor.authorCardoso, Margarida
dc.date.accessioned2015-03-25T16:10:10Z
dc.date.available2015-03-25T16:10:10Z
dc.date.issued2008
dc.descriptionResumo de comunicação oral em póster apresentado em COMPSTAT2008 - 18th International Conference on Computational Statistics, Porto, Portugal, 24 a 29 de Agosto 2008por
dc.description.abstractThe idea of combining models in Discrete Discriminant Analysis (DDA) is present in a growing number of papers which aim to obtain more robust and more stable models than any of the competing ones. This seems to be a promising approach since it is known that different DDA models perform differently on different subjects (Brito et al.(2006)). In particular, this will be a more relevant issue if the groups are not well separated, which often occurs in practice. In the present work a new methodological approach is suggested which is based on DDA models' combination. The multiclass problem is decomposed into several dichotomous problems that are nested in a hierarchical binary tree (Sousa Ferreira (2000), Brito et al. (2006)) and at each level of the binary tree a new combining model is proposed to derive the decision rule. This combining model is based on two well known models in the literature - the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM) (Celeux and Nakache (1994)). The MATLAB software is used for the algorithms' implementation and the proposed approach is illustrated in a DDA application.por
dc.identifier.citationIn COMPSTAST'2008: Book of abstracts. (2008). Porto: FEPpor
dc.identifier.urihttp://hdl.handle.net/10400.26/8127
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherFaculdade de Economia da Universidade do Portopor
dc.subjectCombining modelpor
dc.subjectDiscrete discriminant analysispor
dc.subjectFirst-order independence modelpor
dc.subjectDependence trees modelpor
dc.titleCombining models in discrete discriminant analysis in the multiclass casepor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlacePortopor
oaire.citation.endPage270por
oaire.citation.startPage270por
oaire.citation.titleCOMPSTAT'2008: Book of abstractspor
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor

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