scikit learn Elastic net
from sklearn.linear_model import ElasticNet
EN = ElasticNet(random_state=0)
EN.fit(X, y)
EN.score(X, y) #Return the mean accuracy on the given test data and labels
EN.predict(X) #Return the predictions
#Regression Metrics
#Mean Absolute Error
from sklearn.metrics import mean_absolute_error
mean_absolute_error(y_true, y_pred)
#Mean Squared Error
from sklearn.metrics import mean_squared_error
mean_squared_error(y_true, p_pred)
#R2 Score
from sklearn.metrics import r2_score
r2_score(y_true, y_pred)
#If you like the answer, please upvote -;)