Suppose we have a regularized linear regression model: \[ \text{argmin}_{\mathbf{w}} \left||\mathbf{Y} - \mathbf{Xw} \right||^2 + \lambda \|\mathbf{w}\|_1. \] What is the effect of increasing \( \lambda \) on bias and variance?
(a)] Increases bias, increases variance
(b)] Increases bias, decreases variance
(c)] Decreases bias, increases variance
(d)] Decreases bias, decreases variance
(e)] Not enough information to tell