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This repository has been archived by the owner on May 15, 2022. It is now read-only.
Is it possible to use chantilly for unsupervised learning models (anomalies) and timeseries forecast models, thus without necessarily haivng labeled data? which metrics would be meaningful in this case then?
I ask this because i dont see this kind of "flavors" within the chantilly list.
And also a side question:
can the chantilly backend store more then one model? is it possible to disable metrics computation for models so that the backend does not overload? i have applications in mind with dozens of models at the same time. Is Chantilly suitable in that case?
Great stuff
The text was updated successfully, but these errors were encountered:
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Is it possible to use chantilly for unsupervised learning models (anomalies) and timeseries forecast models, thus without necessarily haivng labeled data? which metrics would be meaningful in this case then?
I ask this because i dont see this kind of "flavors" within the chantilly list.
And also a side question:
can the chantilly backend store more then one model? is it possible to disable metrics computation for models so that the backend does not overload? i have applications in mind with dozens of models at the same time. Is Chantilly suitable in that case?
Great stuff
The text was updated successfully, but these errors were encountered: