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Features selection in Discrete Discriminant Analysis

dc.contributor.authorMarques, Anabela
dc.contributor.authorFerreira, Ana Sousa
dc.contributor.authorCardoso, Margarida
dc.date.accessioned2015-03-25T21:26:52Z
dc.date.available2015-03-25T21:26:52Z
dc.date.issued2011-06
dc.descriptionResumo de comunicação em póster apresentada em 14th International Conference on Applied Stochastic Models and Data Analysis (ASMDA2011), Rome, June 7-10 2011por
dc.description.abstractIn discrete discriminant analysis dimensionality problems occur, particularly when dealing with data from the social sciences, humanities and health. In these domains, one often has to classify entities with a high number of explanatory variables when compared to the number of observations available. In the present work we address the problem of features selection in classification, aiming to identify the variables that most discriminate between the a priori defined classes, reducing the number of parameters to estimate, turning the results easier to interpret and reducing the runtime of the methods used. We specially address classification using a recently methodological approach based on a linear combination of the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM). Data of small and moderate size are considered.por
dc.identifier.citationIn Book of abstracts of the 14th Applied Stochastic Models and Data Analysis International Conference (ASMDA2011). Rome, 2011por
dc.identifier.urihttp://hdl.handle.net/10400.26/8134
dc.language.isoengpor
dc.peerreviewedyespor
dc.subjectDiscrete Discriminant Analysispor
dc.subjectCombining modelspor
dc.subjectDependence Trees modelpor
dc.subjectFirst Order Independence modelpor
dc.subjectHierarchical Coupling procedurepor
dc.subjectVariable selectionpor
dc.titleFeatures selection in Discrete Discriminant Analysispor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceRomepor
oaire.citation.titleBook of abstracts of the 14th Applied Stochastic Models and Data Analysis International Conference (ASMDA2011)por
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor

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