lironber / goad Goto Github PK
View Code? Open in Web Editor NEWOfficial implementation of "Classification-Based Anomaly Detection for General Data" by Liron Bergman and Yedid Hoshen, ICLR 2020.
License: Other
Official implementation of "Classification-Based Anomaly Detection for General Data" by Liron Bergman and Yedid Hoshen, ICLR 2020.
License: Other
Hello,
First of all, thanks for releasing the codebase for your paper. I would like to clarify the definition of contamination ratio
as I found they are inconsistent between the paper description and the code.
In the paper page 8, it is told that "To evaluate the robustness of our method to this unsupervised scenario, we analysed the KDDCUP99 dataset, when X% of the training data is anomalous."
In your implementation, however, c_percent
of samples from anomaly set is sampled and included to the training data.
n_contaminated = int((c_percent/100)*len(anom_samples))
This seems inconsistent with the description in the paper as normal and anomaly dataset sizes are not equal (e.g., for KDD, there are 4x more normal data than anomaly, so the contamination ratio should be 4x smaller than c_percent
if following the description in the paper).
It would be great if this can be clarified. Also, due to this inconsistency, it is difficult to reproduce the contaminated data results on KDDRev or Arrhythmia. It would be great if authors can provide the code that generates the train/val splits for other datasets as well.
I get it
During the training you perform the transformation, and then sum the means per transformation within the batch:
for i in range(0, len(train_xs), self.batch_size):
...
tc_zs, ce_zs = self.netC(xs)
sum_zs = sum_zs + tc_zs.mean(0)
...
means = sum_zs.t() / n_batch
However, the self.netC
changes between batches, so as far as I can tell, means
consists of sums over the outputs of different networks.
Am I wrong?
Thanks!
I use half the number of transforms(72->36) and I find different classes are affected differently
Hi, lironber, I reproduce the experiment on Fashion-mnist, but it fails to close to your results in paper, can you share me the setting about Fashion-mnist ? Thank you!
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