Add support for sample_weights in LinearRegression #4428
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dantegd
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Dec 13, 2021
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lowener
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improvement
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CI Failure on |
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rerun tests |
cjnolet
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Jan 31, 2022
| @@ -62,7 +67,8 @@ void olsFit(const raft::handle_t& handle, | |||
| bool fit_intercept, | |||
| bool normalize, | |||
| cudaStream_t stream, | |||
| int algo = 0) | |||
| int algo = 0, | |||
| math_t* sample_weight = nullptr) | |||
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Not something you need to change in this PR, but it would be nice to start adopting std::optional for arguments like these. Becomes self-documenting as well.
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I agree so I started to make the change but I saw that std::optional support on Cython is very recent and will be added to version 0.30. For the moment we're using version 0.29 so the adoption of std::optional on Python-facing functions should maybe wait a bit more.
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Needed for rapidsai/cuml#4428 Authors: - Micka (https://github.com/lowener) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: #514
dantegd
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Mar 8, 2022
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vimarsh6739
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Oct 9, 2023
Closes rapidsai#4031. Scikit-learn is rescaling the data ([here](https://github.com/scikit-learn/scikit-learn/blob/0d378913be6d7e485b792ea36e9268be31ed52d0/sklearn/linear_model/_base.py#L313)) to take into account the sample_weight parameter. Authors: - Micka (https://github.com/lowener) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4428
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Closes #4031.
Scikit-learn is rescaling the data (here) to take into account the sample_weight parameter.