ML development risks · Question 44 of 60
Two training runs with identical configuration yield slightly different accuracy values, and a developer draws far-reaching conclusions about a hyperparameter change from this. Which risk and which mitigation fit?
2 answers are correct. Hard
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Answer
- A Incorrect interpretation of test results due to the stochastic learning process
- C ML functional performance testing with statistically defined criteria
Explanation
The stochastic nature of the learning process can lead to incorrect interpretation of test results. The mitigation is ML functional performance testing, which measures performance statistically with a margin of error and confidence level instead of comparing individual runs.