Which of the following best describes the objective of lasso regression?

• A. Minimizes the sum of squared residuals with the L1 penalty on coefficients, which can lead to some coefficients being exactly zero.
• B. Minimizes the sum of squared residuals subject to the sum of squares of the coefficients being at most a value.
• C. Minimizes the sum of squared residuals with no penalty.
• D. Maximizes the likelihood with an L1 penalty.

Answer: (A)