What does a validation-error curve above the training-error curve mean?
Question: Answer in one to three sentences using the usual relationship between training and development errors.
Sample answer: It means the development error is larger than the training error. The model is doing better on the training examples than on the development examples, which suggests weaker generalization.
Key points:
- Development error is higher than training error.
- The model fits the training set more closely than the development set.
Rubric: The answer should mention both the higher development error and the model's better performance on the training set.
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