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

I wrote a whole blog post on the matter:
https://blog.ephorie.de/zeror-the-simplest-possible-classifier-or-why-high-accuracy-can-be-misleading

ZeroR, the simplest possible classifier, just takes the majority class as the prediction. With highly imbalanced data you will get a very high accuracy, yet if your minority class is the class of interest, this is completely useless. Please find the details and examples in the post.

Bottom line: when dealing with imbalanced data you can construct overly simple classifiers that give a high accuracy yet have no practical value whatsoever...