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If 1 in 10,000 people have a disease, then a "test" which always reports the patient doesn't have the disease will be correct 99.99% of the time. "99.99% accura
by maxbond 2mo ago
If 1 in 10,000 people have a disease, then a "test" which always reports the patient doesn't have the disease will be correct 99.99% of the time. "99.99% accuracy" should be "looked at with skepticism" in that it doesn't tell you what you need to know to understand the quality of a a test for a rare disease (a classifier under conditions of severe class imbalance); at a minimum, you would want to understand it's false positive and false negative rate, not (just) it's overall error rate.
See example "A": https://en.wikipedia.org/wiki/Base_rate_fallacy https://en.wikipedia.org/wiki/Base_rate_fallacy
- elendilm 2mo agoIf only stating the obvious was a fallacy :) You appear not to have understood probability theory my friend. You will never get 100% in this universe for anything. What if "its a simulation" or "a dream" arguments ensures you never acheive 100%. Bayes probability theory will be a good start for you. https://en.wikipedia.org/wiki/Bayes%27_theorem https://en.wikipedia.org/wiki/Bayes%27_theorem
- maxbond 2mo agoWell, I do agree that all measurements contain error, but the point wasn't that the error rate would be greater than 0% but that a single headline summary of error can't always distinguish between good and bad tests.