NO.PZ2021083101000018
问题如下：
Rivera suggests adjusting the model’s hyperparameters to improve performance.
Achler runs a grid search that compares the difference between the prediction error on both the training and the cross-validation datasets for various combinations of hyperparameter values. For the current values of hyperparameters, Achler observes that the prediction error on the training dataset is small, whereas the prediction error on the cross-validation dataset is significantly larger.
Based on Achler’s grid search analysis, the current model can be characterized as:
选项：
A.underfitted
having low variance
exhibiting slight regularization
解释：
C is correct.
Slight regularization occurs when the prediction error on the training dataset is small, while the prediction error on the cross- validation data set is significantly larger. This difference in error is variance. High variance error, which typically is due to too many features and model complexity, results in model overfitting.
A is incorrect. The current model has high variance which results in model overfitting, not underfitting.
B is incorrect. The difference between the prediction error on the training dataset and the prediction error on the cross-validation dataset is high, which means that the current model has high variance, not low.
老师，请问正则化是什么意思呢，正则化可以降低overfitting吗？
