Case context: A machine-learning team has plotted dev error against the amount of training data. Team members find it difficult to predict exactly where the dev-error curve would go if they obtained more data.

Question: Diagnose the limitation in the team's analysis and decide which additional plot it should use.

Sample answer: The team is relying only on the dev-error curve, which can be difficult to extrapolate. It should also plot training error because that additional plot can help estimate the impact of adding more data.

Key points:

• The current analysis uses only the dev-error curve.
• The difficulty is extrapolating that curve to more data.
• The team should add a training-error plot.
• Training error can help estimate the effect of adding data.

Rubric: The response should diagnose reliance on dev error alone, state that exact extrapolation is difficult, recommend a training-error plot, and connect that plot to estimating the impact of more data.