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GuansongPang / deviation-network

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection, semi-supervised anomaly detection
GNU General Public License v3.0
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Model performance on backdoor datasets #8

Open cjx9869 opened 3 years ago

cjx9869 commented 3 years ago

Hi,Mr Pang I trained model with default arguments by using the backdoor dataset and get the performance as follows AUC-ROC: 0.7793, AUC-PR: 0.2663 average AUC-ROC: 0.7834, average AUC-PR: 0.2730 I saw a similar question in previous issue and your answer is that perform some standard data prepocessing steps，could you provide specific steps and data process code on github?

GuansongPang commented 3 years ago

Hi,Mr Pang I trained model with default arguments by using the backdoor dataset and get the performance as follows AUC-ROC: 0.7793, AUC-PR: 0.2663 average AUC-ROC: 0.7834, average AUC-PR: 0.2730 I saw a similar question in previous issue and your answer is that perform some standard data prepocessing steps，could you provide specific steps and data process code on github?

The dataset has been released in the repo. Please use the released data. Thanks.