PREDICTING STUDENT DROPOUT RISK IN HIGHER EDUCATION: A MACHINE LEARNING APPROACH
A machine learning-based approach for the early prediction of dropout risk, based on academic, socioeconomic, and demographic variables is proposed, which found the best-performing models were Random Forest and its Balanced Random Forest Classifier variant.
Andres Peralta-Fragozo, Juan-Pablo Hoyos-Sánchez
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