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Why is accuracy not the best measure for assessing classification models?

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This is a general question that was asked indirectly multiple times in here, but it lacks a single authoritative answer. It would be great to have a detailed answer to this for the reference.

Accuracy, the proportion of correct classifications among all classifications, is very simple and very "intuitive" measure, yet it may be a poor measure for imbalanced data. Why does our intuition misguide us here and are there any other problems with this measure?


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