A gradient boosting model optimized for speed and performance. Ideal for structured data with high-dimensional features. Trained to predict crop yield based on climate features.
Captures feature interactions with boosted trees. Regularization makes it robust for overfitting.
1import joblib
2model = joblib.load("xgboost_model.pkl")
3y_pred = model.predict(X_test)
