FBeta score in fastai: 'macro' vs 'weighted'

[Pomo (Malcolm McLean)]

Hi. This post might show the cause of the error you are getting.

Making metrics work for NaNs

I ran into a case recently where I wanted to print precision and fbeta values on a highly unbalanced dataset with a large number of classes. Unlike the sklearn equivalents, the fastai metrics don’t seem to have a way of handling cases where these might be NaN, e.g. a precision score of 0/0. While I was able to overcome this for myself by just overriding the classes, this seems like a simple thing to allow for. A possible way of handling this is to just insert the line prec[prec != prec] = 0 in t…