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

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

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 strengt...

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Bibliographic Details
Main Authors: Ummey Hany Ainan, Lip Yee Por, Yen-Lin Chen, Jing Yang, Chin Soon Ku
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Bankruptcy forecasting
predictive analytics
ensemble learning
hyperparameter tuning
machine learning
Online Access:https://ieeexplore.ieee.org/document/10399785/

Internet

https://ieeexplore.ieee.org/document/10399785/

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