Predicting Client attrition through Supervised learning in weight management courses.

Abstract: This project explores the prediction of client dropout from a weight management program using machine learning algorithms. The project also explores clients survival analysis.

Objectives:

1. Predict client dropout using supervised machine learning techniques like random forests, Artificial Neural networks, Naieve bayes and Logistic regression.
2. Survival analysis for understanding client dropout through kaplan-mier curves and COX's proportionality hazards model

Methodology