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Unable to reproduce results for DAGMM #60
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Hi @jonomon, there can be some subtle differences in the way precision/recall are computed, the way the detection threshold is chosen, and how the model handles point data (which the Thyroid dataset is) vs time series data. Before anything else, you should try to use |
Hi @aadyotb Thank you for the reply. Using
It seems like it help too much. As a side note, both the Autoencoder and VAE achieved comparable results on the Thyroid dataset out of the box.
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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 detection." International conference on learning representations. 2018.
I used the following configuration:
and only managed to get the following results on the Thyroid dataset (.mat obtained from http://odds.cs.stonybrook.edu):
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