Kadaj13
Kadaj13

Reputation: 1551

When to use L2 regularization

We know that L1 and L2 regularization are solutions to avoid overfitting.

L1 regularization, can lead to sparsity and therefore avoiding fitting to the noise. However, L2 does not.

So I wonder when there is a need to use L2 regularization?

Upvotes: 1

Views: 569

Answers (1)

Dawei Wang
Dawei Wang

Reputation: 174

L2 penalizes the entire weight coefficients but L1 penalizes some. So, L2 is good for multicollinear inputs and L1 is good for feature selection.

Upvotes: 1

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