🔁 Gradient Boosting Regressor
Trained using Scikit-learn's Gradient Boosting Regressor. Performs sequential boosting to improve performance iteratively. Trained to predict crop yield based on climate features.
📦 File
gradient_boosting_model.pkl
🧠 Use Case
Effective for handling complex relationships and interactions in moderate-sized datasets.
⚙️ Model Info
- Estimator: GradientBoostingRegressor
- Loss: Squared Error
- Learning Rate: Default
📊 Performance
- RMSE: 21465.13
- MAE: 13028.23
- R² Score: 0.93
- MAPE: 30.02%
💡 Usage
import joblib
model = joblib.load("gradient_boosting_model.pkl")
y_pred = model.predict(X_test)