If you want to reduce variance and extra computation is acceptable, which adjustment is usually preferred over shrinking the model?

Reducing a model’s size is usually the first choice for lowering variance when other options are available.

When trying to reduce variance, adding _____ is usually a better first step than simply shrinking the model.

Match each variance-control idea with its best description.

Arrange the steps for handling a model that appears to have high variance.

Why might a practitioner reduce model size even when another approach would better address variance?

Model Capacity and Variance

A smaller model is most useful when _____ training is the main goal, rather than only trying to lower variance.

Arrange the reasoning used to decide whether shrinking a model is a good response to high variance.

When Should You Shrink a Model Instead of Regularizing It?

Choosing a Variance Reduction Strategy for a Speech Model with Slow Training

When a Smaller Model Is a Reasonable Variance Fix