Question: The default is penalty = l 2 . Why would using L 2 regularization potentially improve your model s performance against penalty = None? Under

The default is penalty=l2. Why would using L2 regularization potentially improve your models
performance against penalty=None?
Under what circumstances might L1 regularization be more beneficial than L2?
How does the Elastic Net regularization combine the benefits of L1 and L2 regularization? Why might you choose it over L1 or L2 alone?

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