When we use SVM to do classification, we usually will use this kind of code:
We all know the classifier was using probability to make sure if the predict_label is positive or negative, which is according to thresholds. And with each threshold, we can get a group of sensitivity and specificity, thus we can draw an ROC curve.
My question is the accuracy from the output, we always get a specific number, which is also called ACC. So which threshold is this specific number based on?