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Hi @GuansongPang, I have another question regarding the anomaly contamination level setting on the unlabeled training dataset.
Since we have this feature on the model during the training process (assuming that we have anomalous data on the unlabeled training dataset), does that mean the model can also see which unlabeled data instances that tend to be "anomalous" (have high anomaly score) on the testing dataset?
Thank you.
The text was updated successfully, but these errors were encountered:
Thank you for the answer @GuansongPang, I also interested to understand further about your work in this paper. Would mind publishing the official code for this one? Thank you in advance
Hi @GuansongPang, I have another question regarding the anomaly contamination level setting on the unlabeled training dataset.
Since we have this feature on the model during the training process (assuming that we have anomalous data on the unlabeled training dataset), does that mean the model can also see which unlabeled data instances that tend to be "anomalous" (have high anomaly score) on the testing dataset?
Thank you.
The text was updated successfully, but these errors were encountered: