Can Different Error Problems Appear Separately?
Question: In machine learning development, do high avoidable bias, high variance, and data mismatch have to appear together, or can a model have only some of them?
Sample answer: They do not have to appear together. A model may show any combination of these three problems, including just one problem, two problems, or all three, depending on the model design and the data situation.
Key points:
- High avoidable bias, high variance, and data mismatch are not required to occur at the same time.
- Any subset of the three problems can occur.
- A model may have one, two, or all three issues.
Rubric: The answer should say that the three error sources are not tied to one another and that a model can exhibit any subset or combination of avoidable bias, variance, and data mismatch.
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