Predicting credit default probabilities using machine learning techniques in the face of unequal class distributions
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References listed on IDEAS
- Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
- Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
- B Baesens & T Van Gestel & S Viaene & M Stepanova & J Suykens & J Vanthienen, 2003. "Benchmarking state-of-the-art classification algorithms for credit scoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 627-635, June.
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More about this item
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-BIG-2019-08-26 (Big Data)
- NEP-CMP-2019-08-26 (Computational Economics)
- NEP-PAY-2019-08-26 (Payment Systems & Financial Technology)
- NEP-RMG-2019-08-26 (Risk Management)
- NEP-URE-2019-08-26 (Urban & Real Estate Economics)
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