Which mathematical technique forms the foundation of most modern retail churn prediction models?

In today's competitive retail landscape, mathematics plays a crucial role in predicting customer churn. Advanced statistical models and machine learning algorithms help retailers identify at-risk customers before they leave. This poll tests your knowledge about the mathematical foundations behind modern retail churn prediction systems that transform raw customer data into actionable insights.

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Logistic Regression with regularization penalties
Simple moving averages across quarterly sales
Euclidean distance clustering of demographic data
Geometric mean calculations of purchase frequency