Why add a training-error curve?
Question: Answer in one to three sentences: What weakness of looking only at the dev-error curve motivates also plotting training error?
Sample answer: The dev-error curve alone can be hard to project forward, so it does not clearly show what will happen as more data are added. Plotting training error gives another signal that helps estimate how performance changes with additional data.
Key points:
- Dev error by itself may be difficult to project
- Training error adds information about the effect of more data
Rubric: The answer should mention that the dev-error curve alone is hard to extrapolate and that training error is added to help estimate the impact of more data.
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Related
More Data Often Raises Training Error
Training Set Error Is Usually Lower Than Dev Set Error
Why plot training error when judging whether more data might improve a model?
A development-error curve computed by itself can be hard to project to much larger training sets.
The extra plot used to judge whether more data will help is _____.
Match each learning-curve element to its use when thinking about the value of additional data.
Arrange the steps for judging whether more data may help a model.
How does training error help assess the value of more data?
Estimating the Benefit of More Data
Why add a training-error curve?
What extra plot helps judge the value of collecting more data?
Training loss can help interpret a validation-loss curve when estimating the value of more data.