ON THE SELECTED METHODS FOR EVALUATING CLASSIFICATION MODELS

Abstract

Traditional 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.