Question: In a short analytical response, explain how a simple bias/variance diagnosis leads to different remedies for each problem.

Sample answer: The diagnosis points to different actions depending on the source of the error. If a model has high avoidable bias, a common response is to make the model more expressive, for example by adding more layers or hidden units to a neural network. If the model has high variance, a common response is to expand the training set so the model sees more examples. In other words, the remedy depends on whether the main issue is bias or variance.

Key points:

• High avoidable bias is addressed by increasing model capacity.
• Adding layers or hidden units is one way to increase neural-network capacity.
• High variance is addressed by using more training data.
• The appropriate fix depends on which problem is diagnosed.

Rubric: A strong response correctly matches each problem with its remedy, gives a valid example of increasing model capacity, and clearly states that the choice of action depends on the diagnosis.