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dc.contributor.authorMisztal, Małgorzatapl_PL
dc.date.accessioned2015-12-02T16:00:07Z
dc.date.available2015-12-02T16:00:07Z
dc.date.issued2014pl_PL
dc.identifier.issn0208-6018pl_PL
dc.identifier.urihttp://hdl.handle.net/11089/14865
dc.description.abstractTraditional measures for assessing the performance of classification models for binary outcomes are the ROC curve and the area under the ROC curve (AUC).Reclassification tables (Cook, 2008), net reclassification improvement (NRI) and integrated discrimination improvement (IDI) (Pencina et al., 2008) or decision – analytic measures with decision curve analysis (Vickers Elkin, 2006) have been recently proposed for evaluating the predictive ability of classifiers.This paper analyzes the measures mentioned above with some credit taking application. en_US
dc.language.isoenen_US
dc.publisherWydawnictwo Uniwersytetu Łódzkiegoen_US
dc.relation.ispartofseriesActa Universitatis Lodziensis, Folia Oeconomica; 302pl_PL
dc.titleON THE SELECTED METHODS FOR EVALUATING CLASSIFICATION MODELSen_US
dc.typeArticleen_US
dc.contributor.authorEmailmmisztal@uni.lodz.plpl_PL


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