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ddi

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This project explores how higher education enrollment data can be leveraged to predict whether students are likely to graduate, remain enrolled, or drop out. Using the UCI “Predict Students’ Dropout and Academic Success” dataset (N = 4,424). Random Forest models were trained and evaluated to identify early indicators of student risk.

  • Updated Oct 3, 2025

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