Advanced Machine Learning Feature Engineering Toolkit

Create a comprehensive feature engineering framework specifically designed for scientific research domains. The toolkit must support automatic feature selection, dimensionality reduction, and handle high-cardinality categorical variables common in experimental datasets. Implement statistical significance testing, handle missing data strategically, and provide visualization methods for feature importance. Include support for domain-specific transformations like log-normalization for biological measurements and robust scaling techniques for multi-modal scientific data.