# Import mean_squared_error
from sklearn.metrics import mean_squared_error
# Compute R-squared
r_squared = reg.score(X_test, y_test)
# Compute RMSE
rmse = mean_squared_error(y_test, y_pred, squared=False)
# Print the metrics
print("R^2: {}".format(r_squared))
print("RMSE: {}".format(rmse))