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Semi-Supervised Learning Classification Based on Generalized Additive Logistic Regression for Corporate Credit Anomaly Detection

  • Published:2020 Issue: Volume:8 Page:199060-199069
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Han SongORCID

Funder

Beijing Social Science Fund Project

Beijing Education Commission Social Science Program Project

Youth Top-Notch Talent Cultivation Plan of Beijing Municipal Colleges and Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 6 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. Tri-XGBoost model improved by BLSmote-ENN: an interpretable semi-supervised approach for addressing bankruptcy prediction;Knowledge and Information Systems;2024-04-22

2. Credit risk assessment of small and micro enterprise based on machine learning;Heliyon;2024-03

3. Enhancing Enterprise Credit Risk Assessment with Cascaded Multi-level Graph Representation Learning;Neural Networks;2024-01

4. Rare Event Classification Based on Binary Generalized Extreme Value-Additive Models;2023 6th International Conference on Information and Communications Technology (ICOIACT);2023-11-10

5. Comparison of Different Machine Learning Approaches to Text Classification;2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus);2022-01-25
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