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[FEA] Support set_output for transformers. #5645

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trivialfis opened this issue Nov 6, 2023 · 0 comments
Open

[FEA] Support set_output for transformers. #5645

trivialfis opened this issue Nov 6, 2023 · 0 comments
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? - Needs Triage Need team to review and classify cuml-cpu feature request New feature or request

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scikit-learn has a method for transformers to set the output type, similar to what cuml does with the output_type parameter. See https://scikit-learn.org/stable/auto_examples/miscellaneous/plot_set_output.html for details.
@trivialfis trivialfis added feature request New feature or request ? - Needs Triage Need team to review and classify labels Nov 6, 2023
@trivialfis trivialfis mentioned this issue Nov 7, 2023
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rapids-bot bot pushed a commit that referenced this issue Nov 21, 2023
@trivialfis
Basic implementation of OrdinalEncoder. (#5646)
21fbf04 
- Implement `OrdinalEncoder`.
- Implement dask version.
- Fix dask transformers with DataFrame input by using `dask_cudf` to construct return df.

Some other scikit-learn features are not available yet, for instance, `encoded_missing_value`, `min_frequency`, and `max_categories`.

The implementation is mostly based on the existing one hot encoder and label encoder.

I'm a bit confused by the `output_type` parameter and not sure how strictly it's enforced. I looked around, it seems some estimators can ignore this parameter in their returns. Would be great if there's a guideline on how to handle this parameter, along with #5645 .

Close #4456 .

Authors:
  - Jiaming Yuan (https://github.com/trivialfis)
  - Simon Adorf (https://github.com/csadorf)

Approvers:
  - Simon Adorf (https://github.com/csadorf)

URL: #5646
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