Carte Recent Methods from Statistics and Machine Learning for Credit Scoring Anne Kraus

Recent Methods from Statistics and Machine Learning for Credit Scoring

Autor: Anne Kraus
Limbă: engleză
Legare: Carte broșată
Editura: Cuvillier
Disponibilitate: În depozitul extern
Expediem în 8-11 zile
157.50 lei
Credit scoring models are the basis for financial institutions like retail and consumer credit banks...

Informații despre carte

Autor
Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2014
Pagini
166
EAN
9783954047369
ISBN
3954047365
Enbook ID
12828582
Editura
Greutate
204
Dimensiuni
148 x 210 x 9

Descriere completă

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.

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