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Exact(60)
So there are 299 + 15 positive tests, but only 15 out of 314 are true positives.
Or do you just want an even more stupidly accurate imaginary test, without sacrificing true positives?
true positives.
where precision = # True positives # True positives + # False positives recall = # True positives # True positives + # False negatives.
Many true positives are missed.
True positives are identified with 77% accuracy.
frames labelled as extreme are true positives.
true positives or truly detected damages.
Sensitivity was defined as: (number of true positives)/(number of true positives + number of false negatives).
Thus, it highlights true positives by downplaying false positives.
It might also remove short duration true positives like bend.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com