I've seen some jupyter notebooks that seem to combine
cross_val_score, and I'm confused what the point is.
Usually the working flow looks like:
alpha = [some array of alpha values] lasso = LassoCV(cv=5, alphas=alphas) cross_val_score(lasso, X_train, y_train ,cv=5)
What is the point of using
cross_val_score if there's already CV embedded within LassoCV?