How to compute False Accept and False reject rates using one class SVM? I have a user data with around 70000 samples. I am trying to apply one class SVM here. The number of -1 values obtained are 12765 and the rest are displayed as 1. From these values obtained, how do I compute False Accept Rate ?
How to compute False Accept and False reject rates using one class SVM Python
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You can compute it with the help of Confusion matrix.
You can also find the original answer here