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Human Level Proxy for Bayes Error

To find a reasonable proxy for Bayes error, you should clearly identify what the purpose of your human level performance should be. For example, since doctors have an error of 0.5%, in a given problem we would define 0.5% as the human level error as a proxy for Bayes error. The more specific in what you are defining, the better your outcome, e.g., the error rate by doctors who are above 50 years old and specialize in brain surgery.

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