Dynamic Student Performance Predictive Dashboard with Machine Learning

Create a comprehensive Python-based predictive analytics dashboard using scikit-learn and pandas that forecasts individual student performance risks. The system should integrate historical academic data, attendance records, and extracurricular engagement metrics to generate early warning signals for potential academic underperformance. Develop a modular Flask web application that allows administrators to configure risk thresholds, visualize predictive models, and generate automated intervention recommendations. Include robust data preprocessing techniques, handle missing values strategically, and implement at least three machine learning algorithms for cross-validation.