Update dependency scikit-learn to v1.9.0

[renovate]

This PR contains the following updates:

Package	Change	Age	Confidence
scikit-learn (changelog)	==1.8.0 → ==1.9.0
scikit-learn (changelog)	==1.7.2 → ==1.9.0

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Warning

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Release Notes

scikit-learn/scikit-learn (scikit-learn)

v1.9.0

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[david-cortes-intel]

Suggested change

	scikit-learn==1.9.0 ; python_version <= '3.10'
	scikit-learn==1.7.2 ; python_version <= '3.10'

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[ethanglaser]

/intelci: run

[ethanglaser]

@david-cortes-intel looks like there is private CI fail related to

scikit-learn-intelex/sklearnex/svm/tests/test_svm.py

Line 555 in a404684

if X_xp is torch and (y_xp is pd or w_xp is pd):

(see GPU test runs, NameError: name 'torch' is not defined)

[david-cortes-intel]

@david-cortes-intel looks like there is private CI fail related to

scikit-learn-intelex/sklearnex/svm/tests/test_svm.py

Line 555 in a404684

if X_xp is torch and (y_xp is pd or w_xp is pd):

(see GPU test runs, NameError: name 'torch' is not defined)

Should be fixed here:
#3232

[ethanglaser]

/intelci: run

[renovate]

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You can manually request rebase by checking the rebase/retry box above.

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[ethanglaser]

/intelci: run

[ethanglaser]

Tests were failing in the CondaRecipe due to numpy 1.26 being installed, leading to failures in the tests that I've since updated to have numpy version checks. The CI is now green but important to note that numpy 1.26 is still getting installed in the test step of conda recipe. This can be directly addressed by adding in a lower limit to numpy version (ie numpy >=2,<3) but considering we support some numpy 1.X versions I am not forcing that here. Open question on whether we want to ensure the single CondaRecipe CI run uses a more relevant numpy version in test step, but planning to merge this as is.

[ethanglaser]

Something is crashing in spmd tests. Looking into it.

[ethanglaser]

reproduced but wont have fix til monday