Ms. SK. Raqeeba

Bridging Scalability and Interpretability in AutoML Via Feature Engineering

Experimental evaluation on the Madelon dataset indicates that the automated and interpretable pipeline performs comparably to, and in some respects favourably against, baseline feature engineering approaches, demonstrating the practical effectiveness of combining scalable feature generation with interpretable AutoML.