Featurewiz-Polars: A Robust and Scalable Solution for Feature Selection with XGBoost

Featurewiz-Polars is a tool for automated feature selection that integrates with XGBoost. It simplifies the feature selection process and ensures efficient, scalable implementation, especially for large datasets. The post explains how to use Featurewiz as a scikit-learn transformer, highlights the improved validation-based feature selection method in Featurewiz-Polars, and benchmarks its performance against the mRMR feature selection library.