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 -;)
