Recent Methods from Statistics and Machine Learning for Credit Scoring

Credit scoring models are the basis for financial institutions like retail and consumer credit banks. The purpose of the models is to evaluate the likelihood of credit applicants defaulting in order to decide whether to grant them credit. The area under the receiver operating characteristic (ROC) curve (AUC) is one of the most commonly used measures to evaluate predictive performance in credit scoring. The aim of this thesis is to benchmark different methods for building scoring models in order to maximize the AUC. While this measure is used to evaluate the predictive accuracy of the presented algorithms, the AUC is especially introduced as direct optimization criterion.

Weitere Produkte vom selben Autor

krause Gedanken Krause, Anne

25,00 €*
Feld- und Hallenhockey ¿ Das Praxisbuch für Studium, Training und Freizeitsport Krause, Anne, Rehlinghaus, Konstantin, Hillmann, Wolfgang

34,99 €*
When I See Through My Eyes Kraus, Anne Marie

10,50 €*
...wenn ich mal stark bin. Krause, Anne

16,00 €*