An improved boosting based on feature selection for corporate bankruptcy prediction
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
The selection of financial ratios is an important process in failure prediction.
“The selection of the financial ratios is an important process in failure prediction (Wang et al. 2014).”
From Bank failure prediction: corporate governance and financial indicators (2023) · cites this paper as Wang et al. 2014
Cites
The Strength of Weak Learnability
Schapire, R. E. (1990) · Machine Learning · doi:10.1007/bf00116037 · Cited by 4,600 · see citing works
Hansen, L. K., & Salamon, P. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.58871 · Cited by 4,260 · see citing works
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Explainability of Machine Learning Models for Bankruptcy Prediction
Park, M. S., Son, H., Hyun, C., & Hwang, H. J. (2021) · IEEE Access · doi:10.1109/access.2021.3110270 · Cited by 83 · see citing works
Bank failure prediction: corporate governance and financial indicators
Alzayed, N., Eskandari, R., & Yazdifar, H. (2023) · Review of Quantitative Finance and Accounting · doi:10.1007/s11156-023-01158-z · Cited by 23 · see citing works
- Authors
- Wang, G., Ma, J., & Yang, S.
- Affiliations
- Hefei University of Technology (CN)
- City University of Hong Kong (HK)
- Corresponding author
- Wang, Gang
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2014-04
- Volume
- 41
- Issue
- 5
- Pages
- 2353-2361
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2071193822
- Cited by
- 187
- References
- 2
- Citations by year
- 2026: 12 · 2025: 13 · 2024: 11 · 2023: 19 · 2022: 18 · 2021: 22 · 2020: 18 · 2019: 19 · 2018: 17 · 2017: 13 · 2016: 14 · 2015: 7 · 2014: 3 · 2012: 1
- FWCI
- 29.44
- 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 › Accounting › Corporate Insolvency and Governance
- Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
- Keywords
- corporate bankruptcy prediction, boosting, feature selection, ensemble learning, base learners, financial distress
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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