Mitigating Cognitive Biases in Predicting Student Dropout: Global and Local Explainability with Explainable Boosting Machine
This study explores the application of Explainable Artificial Intelligence (XAI) techniques to mitigate cognitive biases in predicting student dropout. Focusing on the Explainable Boosting Machine (EBM), we compare its performance and explainability with Logistic Regression and XGBoost models. While...
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| Main Authors: | , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
Graz University of Technology
2025-08-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/131773/download/pdf/ |
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