Machine Learning Feature Selection for Scientific Datasets

Create an advanced feature selection pipeline specifically tailored for scientific research datasets with high-dimensional complexity. Develop a modular approach that combines statistical feature ranking, mutual information analysis, and domain-specific feature importance scoring. Implement multiple selection strategies including recursive feature elimination, LASSO regularization, and ensemble-based techniques. Include comprehensive visualization tools for explaining feature interactions and predictive power.