Question: In a concise analytical response, explain how the formula distinguishes high avoidable bias from high variance and assigns a remediation to each.

Sample answer: The formula links each diagnosed issue to a different action. For high avoidable bias, it recommends increasing model size, such as adding layers or neurons to a neural network. For high variance, it recommends adding data to the training set. Thus, the selected intervention depends on whether bias or variance is high.

Key points:

• High avoidable bias maps to increasing model size.
• Adding layers or neurons is an example of increasing neural-network size.
• High variance maps to adding training data.
• The remedy depends on the diagnosed issue.

Rubric: A strong response correctly identifies both issue-action mappings, includes the neural-network example where relevant, and clearly explains that the diagnosis determines the remedy.