Score Fusion by Maximizing the Area under the ROC Curve

Villegas Santamaría, MauricioParedes Palacios, Roberto2014-11-112014-11-112009978-3-642-02171-80302-9743https://riunet.upv.es/handle/10251/44043The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02172-5_61Information fusion is currently a very active research topic aimed at improving the performance of biometric systems. This paper proposes a novel method for optimizing the parameters of a score fusion model based on maximizing an index related to the Area Under the ROC Curve. This approach has the convenience that the fusion parameters are learned without having to specify the client and impostor priors or the costs for the different errors. Empirical results on several datasets show the effectiveness of the proposed approach.Reserva de todos los derechosLENGUAJES Y SISTEMAS INFORMATICOSScore Fusion by Maximizing the Area under the ROC CurveCapítulo de libro10.1007/978-3-642-02172-5_61Abierto