Customer Churn Prediction (Logistic Regression)

This repository contains a complete, runnable example showing how Customer Success teams can use Logistic Regression to predict churn probability and act early.

Why this matters

• Outputs probability, not just labels
• Easy to explain to business leaders
• Maps cleanly to CSM playbooks and thresholds

Run

pip install -r requirements.txt
python logreg_churn_end_to_end.py

Output

• Model quality metrics (ROC AUC, PR AUC)
• Example churn probabilities
• Recommended CSM actions
• Saved production-ready pipeline