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Hello,
Thank you for the nice library!
I was just wondering if you managed to reproduce the results in Zong, Bo, et al. "Deep autoencoding gaussian mixture model for unsupervised anomaly detect…
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Hello. Thanks for your great works.
I use Google Colab, and in my Colab notebook, this Error occurs.
`---------------------------------------------------------------------------
AttributeErro…
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I am running dagmm with Kdd - cup dataset and I'm getting negative determinant, which avoid learning
![image](https://user-images.githubusercontent.com/38043000/75901685-95f87b00-5e47-11ea-801d-bec50…
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The network "dagmm" is built using Tensorflow 1.x and it is incompatible to tensorflow 2.x
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I managed to get great result when testing consistently even when DAGMM is untrained. The results look similar to this:
Accuracy : 0.9637, Precision : 0.9573, Recall : 0.9312, F-score : 0.9441
I…
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File "E:\anomaly_detection\dagmm-master\model.py", line 12, in forward l = torch.potrf(a, False) …
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I sincerely apologize for any confusion earlier. Based on the data you provided, the recall for GDN is 68.12, while for DAGMM it's 69.52. Typically, we would bold the higher value, which in this case …
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When I tried to run DGAMM-LSTM on gpu I got the following message:
can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first
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Implement some of these models (probably in this order)
- [x] AE
- [ ] AE ensemble (or maybe KitNet?)
- [x] DAGMM = Deep autoencoding gaussian mixture model for unsupervised anomaly detection. Su…
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Dear author,
Recently, I am reading the paper of the DaGMM model and reproducing your code. A confusion is why the predict samples of high energy as anomalies? As I have known, the energy represents …