from sklearn.ensemble import GradientBoostingRegressor

# Create the model
gradient_boosted = GradientBoostingRegressor()

# Fit the model on the training data
gradient_boosted.fit(X, y)

# Make predictions on the test data
predictions = gradient_boosted.predict(X_test)

# Evaluate the model
mae = np.mean(abs(predictions - y_test))

print('Gradient Boosted Performance on the test set: MAE = %0.4f' % mae)