Student Churn Prediction Model with Probabilistic Forecasting

Construct a probabilistic machine learning model using Bayesian inference techniques in JavaScript to predict student dropout likelihood. Develop a comprehensive scoring system that integrates multiple data signals including attendance, assignment completion rates, forum participation, and historical academic performance. Create an interactive dashboard using Chart.js that visualizes individual student risk profiles and provides actionable intervention recommendations.