Automated Property Valuation Machine Learning Pipeline

Design a comprehensive Python machine learning pipeline using scikit-learn and pandas that predicts property valuations with 90%+ accuracy. The model should incorporate features like neighborhood crime rates, school district ratings, proximity to amenities, square footage, and recent comparable sales. Implement cross-validation, feature importance ranking, and a Flask API endpoint for real-time valuation predictions. Include error handling for edge cases and a robust logging mechanism to track model performance.