Case context: A team examines its learning curves and finds that training error is above its desired performance level. Its dev error is also higher than its training error. The team proposes collecting more training data as its only response.

Question: Using the source observations, diagnose whether the proposal is sufficient and justify your decision.

Sample answer: The proposal is not sufficient. As more training data is added, training error can only stay the same or get worse, so it cannot be expected to fall to the desired level. Because dev error is usually higher than training error—and is higher in this case—more data alone is also not expected to bring dev error to the desired level.

Key points:

• Training error is already above the desired level.
• Adding data cannot lower training error in the stated learning-curve pattern.
• Dev error is higher than training error.
• More data by itself is therefore insufficient.

Rubric: The answer should reject the proposal as sufficient and justify the diagnosis using both the behavior of training error and the relationship between dev and training error.