Comments (3)
pixelsquared
commented on May 18, 2024
1
What about using docker so that all the dependencies would be contained easily with one command?
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evanmiller29
commented on May 18, 2024
1
I think that the list of requirements for the project should be as simple as possible to make development as easy as possible. Could we possibly separate out the DL models into their own package (like tensorflow CPU/GPU)?
The other dependencies are probably fine though.
Just saying that because to enable that functionality it does take a bit of work on the users end, and if it was separate then we could help them through the process a bit more easily.
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yzhao062
commented on May 18, 2024
closed the thread as we have separated dl related libraries out as suggested by Evan.
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Related Issues (20)
- ABOD weighting schemes / not matching the definition? HOT 1
- ROD models: RuntimeWarning: invalid value encountered in divide
- Which algorithms support ‘Semi-supervised Novelty Detection’？
- Support SHAP for model explanation
- Default parameter inconsistent with docs
- different results depending on time-span HOT 2
- saved model size
- Model prediction in Autoencoder does not support adjusting batch size
- False positive warning when manipulating pandas dataframes
- Grateful
- issues about scikit-learn HOT 3
- TOS selection methods and parameter
- Add wheels to PyPI?
- TypeError: SUOD.__init__() got an unexpected keyword argument 'cost_forecast_loc_fit' HOT 2
- DIF model: duplicate normalization
- How will the effectiveness of the model be evaluated, and does the library provide the appropriate methodology? HOT 1
- Quasi-Monte Carlo Discrepancy always predicts an outlier HOT 1
- Current implementation is not compatible with Keras 3 HOT 1
- ECOD and COPOD decision functions switched
- A problem about DeepSVDD
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