# Import
from sklearn import metrics
from sklearn.metrics import r2_score
from sklearn import linear_model

# Fit
regressor = linear_model.ElasticNet(alpha=1, l1_ratio=0.5, normalize=False)
regressor.fit(X_train, y_train)

# Metrics
yhat = regressor.predict(X_test)
print(metrics.mean_squared_error(y_true=y_test, y_pred=yhat))
print(r2_score(y_test, yhat))