The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients
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- Authors
- Yeh, I.-C., & Lien, C.-H.
- Affiliations
- Chung Hua University (TW)
- Thompson Rivers University (CA)
- Corresponding author
- Yeh, I-Cheng
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2009-03
- Volume
- 36
- Issue
- 2
- Pages
- 2473-2480
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2085988980
- Cited by
- 885
- References
- 0
- Citations by year
- 2026: 71 · 2025: 82 · 2024: 99 · 2023: 92 · 2022: 101 · 2021: 113 · 2020: 93 · 2019: 85 · 2018: 57 · 2017: 29 · 2016: 12 · 2015: 12 · 2014: 2 · 2013: 8 · 2012: 11
- FWCI
- 18.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Accounting › Financial Distress and Bankruptcy Prediction
- Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- credit card default, probability of default, prediction accuracy, artificial neural networks, credit risk management, default prediction
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