Modified Stacking Model for crop yield Prediction using L2 Regularization

This paper focuses on evaluating the performance of 11 crops categorized as Kharif and Rabi using the Optimized Stacking Framework (OSF) in comparison to six base machine learning models: Linear Regression (LR), Least Angle Regression (LAR), Decision Trees (DT), Random Forest (RF), XGBoost, and Support Vector Machines (SVM). The Kharif category comprises Rice, Groundnut, Maize, Jowar, Sugarcane,Soyabean, Jute, and Ragi, while the Rabi category includes Bajra, Barley, andWheat.