Machine Learning Feature Pipeline with Automated Data Validation

Create a robust feature engineering pipeline that automatically detects, validates, and transforms raw data sources for machine learning models. Implement statistical anomaly detection, handle missing values with intelligent imputation strategies, and generate a comprehensive data quality report. The pipeline should support multiple input formats, be configurable for different model types, and include automated feature selection and dimensionality reduction techniques.