What is lasso regression?

What is lasso regression?

Approach: Define L1-regularized linear regression.

Linear regression with L1 penalty on coefficients: min_β ||y-Xβ||² + λ∑|β_j|. Encourages sparsity, performs variable selection.

Follow-up: Compare to ridge regression.

Key concepts: L1 regularization, sparsity, variable selection.