Predicting Bond Defaults in China: A Double-Ensemble Model Leveraging SMOTE for Class Imbalance
This study proposes the Double-Ensemble Learning Classification with SMOTE (DELC-SMOTE), a novel hierarchical framework designed to address the critical challenge of severe class imbalance in financial bond default prediction. The model integrates the Synthetic Minority Over-sampling Technique (SMOT...
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| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2026-03-01
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| Colecção: | Big Data and Cognitive Computing |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/2504-2289/10/3/81 |
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