AUROC with M(x) scores? about deep_mahalanobis_detector HOT 3 CLOSED

For example, you have the target labels (0 or 1) of testing data, corresponding, you can get the M(x) of each testing data. With all predicted results and the target labels, you can calculate the AUROC, AUPR_in AUPR_out and some other metrics.

from deep_mahalanobis_detector.

Hello @ForeverPs, thanks for the reply.

Yes, I agree with you. What was confusing me is that M(x) is not a probability. I was convinced that computing the AUROC requires a probability, i.e. a score in [0,1]. But actually I observed that you can compute AUROC also with any kind of predicted score.

from deep_mahalanobis_detector.

Hello @ForeverPs, thanks for the reply.

Yes, I agree with you. What was confusing me is that M(x) is not a probability. I was convinced that computing the AUROC requires a probability, i.e. a score in [0,1]. But actually I observed that you can compute AUROC also with any kind of predicted score.

Yes, you are right. This metric is based on sorting.

from deep_mahalanobis_detector.