Problem 2 (4 pts). The plot below shows the training and validation r-squared scores of a ridge regression model for varying values of the rgularization hyperparameter. State the (approximate) value of a that would produce the model with the best abilitity to generalize. Briefly explain why you selected that value. 0.9 Training Validation 0.8 0.7 0.6 -Squared 0.5 0.4 0.3 0.2 15 2.0 2.5 3.0 -2.0 -1.5 -1.0 -0.5 0.0 0.5 10 log(alpha) Problem 2 (4 pts). The plot below shows the training and validation r-squared scores of a ridge regression model for varying values of the rgularization hyperparameter. State the (approximate) value of a that would produce the model with the best abilitity to generalize. Briefly explain why you selected that value. 0.9 Training Validation 0.8 0.7 0.6 -Squared 0.5 0.4 0.3 0.2 15 2.0 2.5 3.0 -2.0 -1.5 -1.0 -0.5 0.0 0.5 10 log(alpha)