Judging Avoidable Bias from the Training Set
A handwritten-form classifier makes 16% error on its training set. The lowest achievable error on the task is estimated at 4%. Which conclusion is best supported?
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A model with 8% training error and 7% best achievable error shows strong evidence of high bias.
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Related
A model with 8% training error and 7% best achievable error shows strong evidence of high bias.
Room to Improve When the Best Possible Error Is Near Zero
Matching Bias Clues to Error Gaps
Diagnosing Bias by Comparing Training Error to a Practical Baseline
Why the Same Training Error Can Mean Different Things
Estimating Bias From Training Error and a Human Performance Baseline
What Does a Large Gap Between Training Error and Best Possible Error Suggest?
How to judge whether there is still room to reduce avoidable bias
Can training error by itself tell you whether a bias-reducing change is worthwhile?