Recent Methods from Statistics and Machine Learning for Credit Scoring
Kraus, Anne
ISBN 10: 3954047365 ISBN 13: 9783954047369
Verlag: Cuvillier Verlag, 2014
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnCredit 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. Bestandsnummer des Verkäufers 74490250
Inhaltsangabe:
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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Titel: Recent Methods from Statistics and Machine ...
Verlag: Cuvillier Verlag
Erscheinungsdatum: 2014
Einband: Softcover
Zustand: New
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Recent Methods from Statistics and Machine Learning for Credit Scoring
Verlag:
Cuvillier, Cuvillier Jul 2014, 2014
ISBN 10: 3954047365
ISBN 13: 9783954047369
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 166 pp. Englisch. Artikel-Nr. 9783954047369
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