A hybrid KMV model, random forests and rough set theory approach for credit rating-Reference-Cited by-同舟云学术

A hybrid KMV model, random forests and rough set theory approach for credit rating

Published:2012-09 Issue: Volume:33 Page:166-172
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Yeh Ching-Chiang,Lin Fengyi,Hsu Chih-Yu

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference57 articles.

1. Multi knowledge based rough approximations and applications;Abu-Donia;Knowledge-Based Systems,2012

2. E.I. Altman, S. Katz, Statistical bond rating classification using financial and accounting data, in: Proceedings of the Conference on Topical Research in Accounting, New York, US, 1976, pp. 205–239.

3. The pricing of options and corporate liabilities;Black;Journal of Political Economy,1973

4. Bagging predictors;Breiman;Machine Learning,1996

5. Random forest;Breiman;Machine Learning,2001

Cited by 91 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Corporate financial distress prediction in a transition economy;Journal of Forecasting;2024-08-05

2. Credit risk evaluation on technological SMEs in China;Enterprise Information Systems;2024-07-22

3. Evolution of Credit Scores of Enterprises in a Social Network: A Perspective Based on Opinion Dynamics;IEEE Transactions on Computational Social Systems;2024-06

4. Data-driven approach for intelligent tunnel dust concentration prediction;IOP Conference Series: Earth and Environmental Science;2024-05-01

5. Bidirectional Stackable Recurrent Generative Adversarial Imputation Network for Specific Emitter Missing Data Imputation;IEEE Transactions on Information Forensics and Security;2024