Advancing bankruptcy forecasting with hybrid machine learning techniques: Insights from an unbalanced Polish dataset

• Main Authors: Ainan, Ummey Hany, Por, Lip Yee, Chen, Yen-Lin, Yang, Jing, Ku, Chin Soon
• Format: Article
• Published: Institute of Electrical and Electronics Engineers 2024
• Subjects: HG Finance; QA75 Electronic computers. Computer science
• Online Access: http://eprints.um.edu.my/44183/; https://doi.org/10.1109/ACCESS.2024.3354173

The challenge of bankruptcy prediction, critical for averting financial sector losses, is amplified by the prevalence of imbalanced datasets, which often skew prediction models. Addressing this, our study introduces the innovative hybrid model XGBoost+ANN, designed to leverage the strengths of both...