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khalooei / ALOCC-CVPR2018

Adversarially Learned One-Class Classifier for Novelty Detection (ALOCC)
MIT License
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Discriminator Output Confusion #15

Closed lingyi-Yue closed 5 years ago

lingyi-Yue commented 5 years ago

Is the output of the discriminator an anomaly score during the test of anomaly detection? Why is the output of the discriminator a very small value when I am testing, on the order of e-9 to e-20?

tiandamiao commented 5 years ago

I have the same problem. Have you solved it?

cod3r0k commented 5 years ago

Is the output of the discriminator an anomaly score during the test of anomaly detection? Why is the output of the discriminator a very small value when I am testing, on the order of e-9 to e-20?

Of course, yes. I hope the authors answer these questions as soon as possible, but I had the same problem with your mentioned issue, but it depends on our training stop. The GAN training with pure optimization scenarios, has some tricks for stopping criteria. Their idea and implementation was very well. Also, you can find the Adversarial AutoEncoder ALOCC (Generative Probabilistic Novelty Detection with Adversarial Autoencoders) which was the same as pure ALOCC.

khalooei commented 5 years ago

Is the output of the discriminator an anomaly score during the test of anomaly detection? Why is the output of the discriminator a very small value when I am testing, on the order of e-9 to e-20?

I have the same problem. Have you solved it?

Is the output of the discriminator an anomaly score during the test of anomaly detection? Why is the output of the discriminator a very small value when I am testing, on the order of e-9 to e-20?

Of course, yes. I hope the authors answer these questions as soon as possible, but I had the same problem with your mentioned issue, but it depends on our training stop. The GAN training with pure optimization scenarios, has some tricks for stopping criteria. Their idea and implementation was very well. Also, you can find the Adversarial AutoEncoder ALOCC (Generative Probabilistic Novelty Detection with Adversarial Autoencoders) which was the same as pure ALOCC.

Dear @lingyi-Yue @tiandamiao @cod3r0k , As I mentioned in #14, this depended on your configuration, stopping criteria and any other things which I previously answered in #14, #13, #5.