Question: How does L 1 regularization differ from L 2 in terms of feature selection in machine learning? L 1 enhances feature interactions. L 1 can

How does L1 regularization differ from L2 in terms of feature selection in machine learning?
L1 enhances feature interactions.
L1 can lead to sparse models with some feature weights reduced to zero, effectively selecting features.
L2 is primarily used for selecting categorical features.
L1 increases the number of features in the model.
How does L1 regularization differ from L2 in terms of feature

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