Dropout Risk Predictive Intervention Model

Develop a machine learning pipeline to predict student dropout risks with high precision, incorporating non-linear feature interactions and ensemble modeling techniques. Create a comprehensive data preprocessing workflow that handles missing data, normalizes academic performance indicators, and generates actionable risk stratification. Implement using scikit-learn with detailed model interpretability metrics and potential intervention recommendations.