Complex Customer Lifetime Value Prediction Model

Develop a comprehensive Python script using machine learning techniques to calculate customer lifetime value (CLV) for an e-commerce platform. The model should incorporate predictive features including purchase frequency, average order value, customer tenure, and churn probability. Implement advanced feature engineering techniques like polynomial interaction terms and time-decay weighting. Include cross-validation with both linear regression and gradient boosting models, providing confidence intervals and feature importance analysis.