ML development risks · Question 46 of 60
A team chose k-fold cross-validation with an unsuitable split and considers the results reliable. Which mitigation helps against this development risk?
1 answer is correct. Hard
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Answer
- D ML functional performance testing
Explanation
ML functional performance testing is the mitigation against poor selection of the evaluation approach, for example k-fold cross-validation. It checks performance with an independent, representative test dataset against statistically defined criteria.