Repository logo
 
Publication

Discrete discriminant analysis: The performance of combining models

dc.contributor.authorMarques, Anabela
dc.contributor.authorFerreira, Ana Sousa
dc.contributor.authorCardoso, Margarida
dc.date.accessioned2015-03-25T17:13:28Z
dc.date.available2015-03-25T17:13:28Z
dc.date.issued2009-03
dc.descriptionResumo de comunicação oral apresentada em 11th Conference of the International Federation of Classification Societes (IFCS 2009), Dresden, Germany, 13-18 March 2009por
dc.description.abstractThe idea of combinig 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 [1]. This is a particularly relevant issue when the groups are not well separeted, which often occurs in practice. recently, a new methodological approach was proposed based on a linear combination of the First-order Independence Model (FOIM) and the Dependence trees Model (DTM) ([3] and [2]). In the present work we further explore the referred approach. Since FOIM assumes that the P discrete predictive variables are independent in each group and DTM takes the predictors relationships into account, we think that the proposed approach could be sucessfully applied to many real situations. In order to evaluate its performance, we consider both real and simulated data. Furthermore we present comparisons with alternative models performance. According to the training sample size the leave-one-out approach, v-fold cross validation or assessing the error rate in a test sample are considered. The MATLAB software is used for the algorithms' implementation.por
dc.identifier.citationIn Book of abstracts of the 11th Conference of the International Federation of Classification Societes (IFCS 2009). Dresden: Technische Universitätpor
dc.identifier.urihttp://hdl.handle.net/10400.26/8129
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherTechnische Universität Dresdenpor
dc.subjectCombinig modelspor
dc.subjectDependence Trees Modelpor
dc.subjectDiscrete Discriminant Analysispor
dc.subjectFirst Order Independence Modelpor
dc.titleDiscrete discriminant analysis: The performance of combining modelspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceDresdenpor
oaire.citation.endPage95por
oaire.citation.startPage95por
oaire.citation.titleBook of abstracts of the 11th Conference of the International Federation of Classification Societes (IFCS 2009)por
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Resumo_IFCS2009.pdf
Size:
37.62 KB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.85 KB
Format:
Item-specific license agreed upon to submission
Description: