How do I choose the right regularization technique for my model?

How do I choose the right regularization technique for my model?

Choosing the right regularization technique depends on your model type and the nature of your data. Are you using linear regression or a neural network?

I'm using linear regression.

For linear regression, Lasso (L1) and Ridge (L2) are common choices. Lasso can help with feature selection, while Ridge is better for multicollinearity. Do you have a preference?

I think I need feature selection. Should I go with Lasso then?

Yes, Lasso is a great choice for feature selection! It can shrink some coefficients to zero, effectively removing less important features.

What if I have a lot of features and want to keep them all?

In that case, Ridge regression might be more suitable as it keeps all features but reduces their impact. You could also consider Elastic Net, which combines both Lasso and Ridge.