Items related to Recent Methods from Statistics and Machine Learning...
Synopsis
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.
"synopsis" may belong to another edition of this title.
- PublisherCuvillier
- Publication date2014
- ISBN 10 3954047365
- ISBN 13 9783954047369
- BindingPaperback
- LanguageEnglish
- Number of pages166
Search results for Recent Methods from Statistics and Machine Learning...
Stock Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Print on DemandSeller: PBShop.store US, Wood Dale, IL, U.S.A.
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9783954047369
Quantity: Over 20 available
Stock Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # ABLIING23Apr0316110171956
Quantity: Over 20 available
Seller Image
Recent Methods from Statistics and Machine Learning for Credit Scoring (Paperback or Softback)
Published by
Cuvillier 7/8/2014, 2014
ISBN 10: 3954047365
ISBN 13: 9783954047369
New
Paperback or Softback
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
Seller rating 5 out of 5 stars
Paperback or Softback. Condition: New. Recent Methods from Statistics and Machine Learning for Credit Scoring 0.45. Book. Seller Inventory # BBS-9783954047369
Quantity: 5 available
Stock Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9783954047369
Quantity: Over 20 available
Stock Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Print on DemandSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9783954047369
Quantity: Over 20 available
Stock Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Seller: Chiron Media, Wallingford, United Kingdom
Seller rating 5 out of 5 stars
PF. Condition: New. Seller Inventory # 6666-IUK-9783954047369
Quantity: 10 available
Stock Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9783954047369_new
Quantity: Over 20 available
Seller Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 166 pp. Englisch. Seller Inventory # 9783954047369
Quantity: 2 available
Seller Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783954047369
Quantity: 1 available
Seller Image
Recent Methods from Statistics and Machine Learning for Credit Scoring
Published by
Cuvillier Verlag, 2014
ISBN 10: 3954047365
ISBN 13: 9783954047369
New
Kartoniert / Broschiert
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Kartoniert / Broschiert. Condition: New. 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. Seller Inventory # 74490250
Quantity: Over 20 available