Question
Which of the following best describes the minimization of the residual term in a ridge linear regression?
- A. |e|
- B. e
- C. e² Correct
- D. 0
Explanation
Ridge regression minimizes the sum of squared residuals (e²), the ordinary least squares loss, plus an L2 penalty on the size of the coefficients. The absolute value |e| is the loss of least absolute deviations regression, and the L1 penalty belongs to lasso, not ridge. Minimizing the raw residual e is meaningless because positive and negative errors cancel, and zero residuals is not an achievable objective.
