Câu 35: RAI: Risk and Artificial Intelligence

A team builds a predictive model that performs extremely well on the training dataset but shows noticeably worse accuracy on the validation dataset. The team decides to apply ridge regression (L2) regularization before retraining. After doing so, they observe that the validation accuracy improves. Based on this scenario, which aspect of L2 regularization is likely playing a role in improving the model's performance?

1. A. L2 regularization increases model flexibility by allowing larger coefficients.
2. B. L2 regularization reduces model variance by penalizing large coefficients. — đáp án hiện tại
3. C. L2 regularization changes irrelevant features’ coefficients to zero.
4. D. L2 regularization eliminates multicollinearity by removing correlated features.