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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?

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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