Automated Property Valuation Machine Learning Pipeline

Design a comprehensive Python ML pipeline using scikit-learn and pandas that predicts property valuations with 90%+ accuracy. The system must integrate historical sales data, geospatial features, economic indicators, and neighborhood-specific attributes. Implement cross-validation, feature engineering techniques, and create a Flask microservice that allows real-time valuation predictions. Include robust error handling, logging, and a clear model interpretability report showing feature importance.