How do we calculate the f1 score in anomaly detection (using a One-Class-Support Vector Machine(OC-SVM))? I am not sure what is considered as a true positive? Is it if I predict an anomaly and the label is "anomaly" or is it the other case: I predict "no anomaly" and the label is "no-anomaly"?
Assuming we got the following scores:
TP: 68 FP: 1184 TN: 1723 FN: 414
We can calculate the F1 score as follows:
F1 with TP=TP: 0.07843 F1 with TN=TN: 0.68318
Depending on which case I see as the "True Positive", I have two different scores! What is typically reported in scientific papers?