How is dev-set error evaluated and plotted for different training-set sizes when constructing a learning curve?
Question: Briefly explain how you obtain the values for the y-axis when plotting a learning curve by varying training-set sizes.
Sample answer: The values on the y-axis represent the dev-set error. You obtain these values by evaluating separate copies of the algorithm, each trained on a different training-set size, against the dev set.
Key points:
- The y-axis plots dev-set error.
- Dev-set error is calculated by evaluating separate copies of the algorithm trained on different subset sizes.
Rubric: The response must identify dev-set error as the y-axis metric and explain that it is calculated by evaluating the separate algorithm copies trained on the different subset sizes.
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How is dev-set error evaluated and plotted for different training-set sizes when constructing a learning curve?