Learn Before
When Selective Relabeling Is Acceptable
Selective relabeling can be reasonable when you only need a practical result for building a product or application. It becomes a problem when the result will be reported in a research paper or when you need an unbiased estimate of test-set performance.
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Reviewing Only Mistakes Can Skew a Dev Set
When Selective Relabeling Is Acceptable
What problem can occur if you correct only the dev-set examples your model got wrong?
True or False: If you relabel only the validation examples your system missed, the validation result remains an unbiased estimate.
Fixing labels only on the development examples your model misclassifies can introduce bias into evaluation because those examples are not selected at random.
How can selective relabeling skew a development-set score?
Editing Only the Wrongly Labeled Dev Examples Can Skew Your Evaluation
To avoid label-fix bias, review labels on _____ dev examples, not only the ones your model got wrong.
Match each review policy to its impact on validation-set fairness.
Put the label-review workflow in the right order to avoid bias.
What happens to the measured development accuracy if labels are corrected only for examples the model got wrong?
Checking only the dev examples your model got wrong is enough to guarantee an unbiased evaluation set.
Selective relabeling misses examples the classifier gets _____, so some bad labels are never examined.
Match each label-audit term with its meaning.
Put the steps in order to show why correcting only mislabeled mistakes can distort validation results.
Why does correcting only the labels of examples the model got wrong distort measured accuracy?
Why reviewing only mistaken labels can distort validation results
State the main risk of fixing only misclassified dev set labels.
Learn After
When is it acceptable to clean up noisy labels even if the labels are not perfectly objective?
True or False: Correcting labels before reporting results in a research paper can create problematic label-correction bias.
Label-correction bias may be acceptable when the goal is simply to build a _____ or service.
Match each scenario to whether label correction is acceptable.
Order the steps for deciding whether label-based correction is acceptable
Why Label Cleanup Can Be Acceptable in Some Settings
Decide when relabeling bias is acceptable in two planned uses of a result.
When is label correction a poor choice?
A project needs an unbiased held-out accuracy estimate. How should it view relabeling errors in that set?
A small product team and a publishable research study should always handle label fixes in the same way.