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TPR is defined like this:
return t_pos / (t_pos + f_neg)
If both t_pos and f_neg are 0, then numpy produces NaN. But I'd argue that the result should be 0 instead.
t_pos
f_neg
NaN
cc @olliethomas @MylesBartlett
The text was updated successfully, but these errors were encountered:
I know we've spoken about this before.
Conversation from 24th November 2020
oliver 15:40 maybe 0/0 should be 0 :man-shrugging: thomas_k 15:40 I think it’s more informative to report this as nan
and I know we'd discussed it before then too.... Maybe. we should just make it 0
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hm, I see... maybe my past self was right.
I think we should still avoid the division by zero because it produces annoying warnings. We can still return NaN though.
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TPR is defined like this:
If both
t_pos
andf_neg
are 0, then numpy producesNaN
. But I'd argue that the result should be 0 instead.cc @olliethomas @MylesBartlett
The text was updated successfully, but these errors were encountered: