About

SuccessLens is a comprehensive machine learning project that analyzes Zerve platform event data to identify behavioral patterns predicting long-term user success, building a Random Forest classifier (95% accuracy, 0.84+ ROC-AUC) and generating six publication-quality visualizations (ROC curves, confusion matrices, feature importance, success probability distributions) along with detailed behavioral cohort analysis across 5,410 users and 140 engineered features.