Enhancing going concern prediction with Anchor explainable AI and attention-weighted XGBoost
In the rapidly evolving sector of financial analytics, predicting a firm's going concern status accurately is vital for informed user decisions. This study introduces a novel method that synergizes Anchor Explainable Artificial Intelligence (XAI) with an Attention-Weighted Extreme Gradient Boos...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
IEEE
2024
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/43517/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/43517/ http://dx.doi.org/10.1109/ACCESS.2024.3401007 |
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