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In a multi-label or multi-class classification setting, when choosing between a micro or a weighted F1 score, what shall I take into account?

The main upside of choosing macro is that one gets a sense of effectiveness on small classes. Assuming that the small classes are of no importance, how to choose between micro or a weighted F1 score?

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Micro f1 is based on global precision and recall. It treats each test case equally and doesn't give advantages to small classes. I think it's more suitable.

This article "Macro- and micro-averaged evaluation measures" from Vincent Van Asch in U of Antwerp explains many different kinds of f1 scores.

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