£72.65

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Springer Application of AI in Credit Scoring Modeling (BestMasters)

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£73.46 £72.57 £72.76 £72.96 £73.15 £73.35 £73.54 11 August 2026 31 August 2026 20 September 2026 10 October 2026 30 October 2026
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Description

The scope of this study is to investigate the capability of AI methods to accurately detect and predict credit risks based on retail borrowers' features. The comparison of logistic regression, decision tree, and random forest showed that machine learning methods are able to predict credit defaults of individuals more accurately than the logit model. Furthermore, it was demonstrated how random forest and decision tree models were more sensitive in detecting default borrowers.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
08 December 2022
Listed Since
11 November 2022

Barcode

No barcode data available

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