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[ENH] Backend agnostic machine learning models #370

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VibhuJawa opened this issue Jan 14, 2022 · 1 comment · Fixed by #962
Closed

[ENH] Backend agnostic machine learning models #370

VibhuJawa opened this issue Jan 14, 2022 · 1 comment · Fixed by #962
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enhancement New feature or request machine learning Improvements or issues with machine learning functionality

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@VibhuJawa
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Is your feature request related to a problem? Please describe.
As we are working becoming more backend agnostic (GPU/CPU) , we should look into a way of supporting multiple ML backends with minimal code change .

Describe the solution you'd like

We currently have to specify the cuml/sklearn model class. We should look into a way of training models where we detect what the input type is and have the user just specify ‘RandomForest’ and have dask-sql handle inferring the rest of the classname.

So if the training dataframe is on CPU we use sklearn and if it is on GPU we use cuML.

@VibhuJawa VibhuJawa added enhancement New feature or request needs triage Awaiting triage by a dask-sql maintainer machine learning Improvements or issues with machine learning functionality and removed needs triage Awaiting triage by a dask-sql maintainer labels Jan 14, 2022
@sarahyurick
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Now that we are moving away from Dask-ML, we can also look further into doing this.

@randerzander

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Labels
enhancement New feature or request machine learning Improvements or issues with machine learning functionality
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