End-to-end predictive analytics pipeline for student retention using imbalanced academic data, stacked ML models, recall-optimized decision thresholds, and fairness-aware evaluation with cost–benefit analysis.
data-science machine-learning random-forest pca classification ensemble-learning feature-engineering support-vector-machines predictive-analytics fairness imbalanced-data model-evaluation average-precision responsible-ai recall-optimization algorithm-bias
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Updated
Jan 31, 2026 - Jupyter Notebook