Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset-Reference-Cited by-同舟云学术

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Advancing Bankruptcy Forecasting With Hybrid Machine Learning Techniques: Insights From an Unbalanced Polish Dataset

Published:2024 Issue: Volume:12 Page:9369-9381
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ainan Ummey Hany¹,Por Lip Yee¹^ORCID,Chen Yen-Lin²^ORCID,Yang Jing¹,Ku Chin Soon³^ORCID

Affiliation:

1. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia

2. Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei, Taiwan

3. Department of Computer Science, Universiti Tunku Abdul Rahman, Kampar, Malaysia

Funder

Universiti Tunku Abdul Rahman (UTAR) Financial Support for Journal Paper Publication Scheme

Ministry of Education of Taiwan

National Science and Technology Council in Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10399785.pdf?arnumber=10399785

Reference38 articles.

1. Bankruptcy Prediction Using Machine Learning Techniques

2. An overview of bankruptcy prediction models for corporate firms: A Systematic literature review

3. Corporate Bankruptcy Prediction: An Approach Towards Better Corporate World

4. A Machine Learning-based DSS for mid and long-term company crisis prediction

5. Appropriate machine learning techniques for credit scoring and bankruptcy prediction in banking and finance: A comparative study

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