S. Sharma

Explainable machine learning for crop recommendation using statistical validation and SHAP interpretability in South Asian agricultural data

A comprehensive, reproducible ML framework for crop recommendation that integrates comparative feature selection, multi-model benchmarking, statistical significance testing with Nadeau–Bengio correction, and SHAP-based explainability is presented.