Deep learning for credit scoring : do or don’t?
- Author
- Björn Rafn Gunnarsson, Seppe vanden Broucke (UGent) , Bart Baesens, María Óskarsdóttir and Wilfried Lemahieu
- Organization
- Keywords
- Information Systems and Management, Management Science and Operations Research, Modeling and Simulation, General Computer Science, Industrial and Manufacturing Engineering, Decision support systems, Risk analysis, Credit scoring, Deep learning, Bayesian statistical testing, ART CLASSIFICATION ALGORITHMS, DATA MINING METHODS, NEURAL-NETWORKS, OPTIMIZATION, INTELLIGENCE, CLASSIFIERS, MACHINE, DEFAULT, DESIGN, TESTS
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8751959
- MLA
- Gunnarsson, Björn Rafn, et al. “Deep Learning for Credit Scoring : Do or Don’t?” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 295, no. 1, 2021, pp. 292–305, doi:10.1016/j.ejor.2021.03.006.
- APA
- Gunnarsson, B. R., vanden Broucke, S., Baesens, B., Óskarsdóttir, M., & Lemahieu, W. (2021). Deep learning for credit scoring : do or don’t? EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 295(1), 292–305. https://doi.org/10.1016/j.ejor.2021.03.006
- Chicago author-date
- Gunnarsson, Björn Rafn, Seppe vanden Broucke, Bart Baesens, María Óskarsdóttir, and Wilfried Lemahieu. 2021. “Deep Learning for Credit Scoring : Do or Don’t?” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 295 (1): 292–305. https://doi.org/10.1016/j.ejor.2021.03.006.
- Chicago author-date (all authors)
- Gunnarsson, Björn Rafn, Seppe vanden Broucke, Bart Baesens, María Óskarsdóttir, and Wilfried Lemahieu. 2021. “Deep Learning for Credit Scoring : Do or Don’t?” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 295 (1): 292–305. doi:10.1016/j.ejor.2021.03.006.
- Vancouver
- 1.Gunnarsson BR, vanden Broucke S, Baesens B, Óskarsdóttir M, Lemahieu W. Deep learning for credit scoring : do or don’t? EUROPEAN JOURNAL OF OPERATIONAL RESEARCH. 2021;295(1):292–305.
- IEEE
- [1]B. R. Gunnarsson, S. vanden Broucke, B. Baesens, M. Óskarsdóttir, and W. Lemahieu, “Deep learning for credit scoring : do or don’t?,” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 295, no. 1, pp. 292–305, 2021.
@article{8751959,
author = {{Gunnarsson, Björn Rafn and vanden Broucke, Seppe and Baesens, Bart and Óskarsdóttir, María and Lemahieu, Wilfried}},
issn = {{0377-2217}},
journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
keywords = {{Information Systems and Management,Management Science and Operations Research,Modeling and Simulation,General Computer Science,Industrial and Manufacturing Engineering,Decision support systems,Risk analysis,Credit scoring,Deep learning,Bayesian statistical testing,ART CLASSIFICATION ALGORITHMS,DATA MINING METHODS,NEURAL-NETWORKS,OPTIMIZATION,INTELLIGENCE,CLASSIFIERS,MACHINE,DEFAULT,DESIGN,TESTS}},
language = {{eng}},
number = {{1}},
pages = {{292--305}},
title = {{Deep learning for credit scoring : do or don’t?}},
url = {{http://doi.org/10.1016/j.ejor.2021.03.006}},
volume = {{295}},
year = {{2021}},
}
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