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RNN = Recurrent Neural Network
two passes
Precision=TP/(TP+FP) - false positive -> 0
Recall=TP/(TP+FN) - tp -> 0
F1=2Precision⋅Recall/(Precision + Recall)
Accuracy = (TP+TN)/(TP+TN+FP+FN)
false positive false negative
true pred
FP A = pred = A true != A
FN A = true = A pred != A
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