An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior.
The accurate prediction and interpretation of corporate Environmental, Social, and Governance (ESG) greenwashing behavior is crucial for enhancing information transparency and improving regulatory effectiveness. This paper addresses the limitations in hyperparameter optimization and interpretability...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316287 |
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