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ENH add Array API support for`d2_pinball_score` and`d2_absolute_error_score`#31671

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ENH add Array API support for`d2_pinball_score` and`d2_absolute_error_score`#31671

virchan wants to merge4 commits intoscikit-learn:mainfromvirchan:issues/26024/d2_absolute_error_score_and_d2_pinball_score

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virchan commentedJun 28, 2025

Reference Issues/PRs

Towards#26024

What does this implement/fix? Explain your changes.

Adds Array API support ford2_pinball_score andd2_absolute_error_score.

Any other comments?

N/A

add Array API support tod2_absolute_error_score and `d2_pinball_sc…

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…ore`

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github-actionsbot commentedJun 28, 2025•
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virchan changed the title~~add Array API support tod2_absolute_error_score and `d2_pinball_sc…~~ENH add Array API support ford2_pinball_score andd2_absolute_error_score

Jun 28, 2025

add changelog

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virchan added the Array API label

Jun 28, 2025

virchan added2 commits

June 27, 2025 22:25

fix typo

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addd2_absolute_error_score andd2_pinball_score to `test_array_a…

133d82a

…pi_compliance`'s `xfail`.

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Jun 28, 2025

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I think we need to add Array API support for thequantile function to handle cases wheresample_weight isNone. I'll work on that later.

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lucyleeow commentedJun 30, 2025

Scipyquantile now supports array API (but not weights):scipy/scipy#22352

Theirquantile function is probably (?) faster than ours (benchmarking needed) and it would be nice to not maintain another array API function. But it was added after our min scipy.

I'll open an RFC issue about adding quantile to array api extra, it's been on my todo for a while.

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Jun 30, 2025

ENH: addquantiledata-apis/array-api-extra#340

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lucyleeow commentedJun 30, 2025

data-apis/array-api-extra#340 may take a long while, so we should still decide here what we want to do, even if it is 'temporary'.

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virchan commentedJun 30, 2025

Thanks@lucyleeow!

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Jun 30, 2025

Make more of the "tools" of scikit-learn Array API compatible#26024

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OmarManzoor commentedJun 30, 2025•
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Do we really need a dedicated implementation forquantile inarray-api-extra when all the relevant array api libraries support it (I checked that dask and jax also support this aside from cupy and Pytorch)? Maybe all we actually need is a helper that can call the respective function of the library under consideration (Pytorch has a different name for the dim parameter) and simply convert to numpy to handlearray-api-strict.

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lucascolley commentedJun 30, 2025

Do we really need a dedicated implementation for quantile in array-api-extra when all the relevant array api libraries support it

The dedicated implementation should not be too difficult, ashttps://github.com/scipy/scipy/blob/main/scipy/stats/_quantile.py already supports the standard
The delegation to existing libraries you describe can be covered by array-api-extra too:https://github.com/data-apis/array-api-extra/blob/main/src/array_api_extra/_delegation.py

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OmarManzoor commentedJun 30, 2025

The delegation to existing libraries you describe can be covered by array-api-extra too:https://github.com/data-apis/array-api-extra/blob/main/src/array_api_extra/_delegation.py

@lucascolley Thanks for the feedback. I think it makes sense to add it there then. Do we need a new implementation though when we don't really need it? I guess it would require copying the relevant code from scipy?

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lucascolley commentedJun 30, 2025

Do we need a new implementation though when we don't really need it?

Yes, it is good to future-proof and not rely on existing libraries. cf. Tim's comment over atdata-apis/array-api-extra#340 (comment) let's continue discussion over there