dc.creatorBARAJAS, Freddy Hernandez
dc.creatorMORALES, Juan Carlos Correa
dc.date.accessioned2012-10-20T04:52:24Z
dc.date.accessioned2018-07-04T15:47:27Z
dc.date.available2012-10-20T04:52:24Z
dc.date.available2018-07-04T15:47:27Z
dc.date.created2012-10-20T04:52:24Z
dc.date.issued2009
dc.identifierREVISTA COLOMBIANA DE ESTADISTICA, v.32, n.2, p.247-265, 2009
dc.identifier0120-1751
dc.identifierhttp://producao.usp.br/handle/BDPI/30781
dc.identifierhttp://apps.isiknowledge.com/InboundService.do?Func=Frame&product=WOS&action=retrieve&SrcApp=EndNote&UT=000273181700005&Init=Yes&SrcAuth=ResearchSoft&mode=FullRecord
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1627420
dc.description.abstractIn this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh(-1)-normal multivariate distributions we found that MLR had the better performance.
dc.languagespa
dc.publisherUNIV NAC COLOMBIA, DEPT ESTADISTICA
dc.relationRevista Colombiana de Estadistica
dc.rightsCopyright UNIV NAC COLOMBIA, DEPT ESTADISTICA
dc.rightsrestrictedAccess
dc.subjectLogistic regression
dc.subjectNonparametric discriminant analysis
dc.subjectMultiple classification
dc.titleComparison for three Classification Techniques
dc.typeArtículos de revistas


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