Very Clevery

Student Dropout Risk Prediction After Two Semesters: A Comparative Study Of Logistic Regression, Random Forest, and XGBoost with SHAP

Student dropout requires accurate and explainable early detection so that model outputs can support academic decisions responsibly within an early warning system. This study compares logistic regression, Random Forest, and extreme gradient boosting for student dropout prediction and examines how explainable artificial...