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Author/Affiliation: Mohamad Al MajzoubOpen AccessArticle
11 Pages 
An Ensemble Learning Approach for Student Performance Analysis of a Higher Educational Institute using a SHAP-Based Feature Selection and Optuna Optimization
Abstract:
Forecasting and assessing student performance are crucial for allowing educators to pinpoint deficiencies and promote grade improvement. A thorough comprehension of feature contributions is crucial for improving model interpretability and facilitating informed decision-making in academic institutions. Explainable artificial intelligence encompasses methodologies and strategies designed to deliver transparent and accessible rationales for the decisions rendered by…
Read More(This article belongs to the SP20 (Special Issue on Multidisciplinary Frontiers in Engineering, Computing and Applied Sciences 2026) & Section Artificial Intelligence in Computer Science (CAI))