Feature Selection (Wrapper Methods)

Explore how wrapper methods help in feature selection by iteratively adding or removing features based on model accuracy. Understand techniques like forward selection, backward elimination, exhaustive search, and recursive feature elimination to choose the best feature subset for machine learning models using practical approaches and scikit-learn utilities.