Trying to understand the Fowlkes-Mallows Score I recently bought Chris Albon's ML flashcards and I'm working my way through them. But this one on the Fowlkes-Mallows score has me stumped, as his definitions of false negatives and false positives seem reversed:



If y_hat are my predictions, and I've said that a pair of observations are in the same cluster when they're not, how is that a false negative and not a false positive? 

Of course I read the Wikipedia article and did some Googling, but haven't turned up a clear answer yet. 

Am I misunderstanding? Did he get this wrong?
Yes, its a mistake.

FN: they should be together but you said they are not, you false negatively ordered them to a different class.
FP: they should not be together, but you said they are you false positevly ordered them together