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ENH use utility _check_sample_weight in IsotonicRegression #16322

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Merged
merged 4 commits into from
Jan 30, 2020

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Batalex
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@Batalex Batalex commented Jan 30, 2020

Reference Issues/PRs

Continuation of #16203 so that we can close #15358.

What does this implement/fix? Explain your changes.

This PR's addition is to reorder the sample_weights array as discussed in the original PR.
I force the array to be contiguous otherwise a test would fail locally for this very reason.

Any other comments?

2020 Paris Sprint

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@NicolasHug NicolasHug left a comment

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Nit but LGTM, thanks @Batalex

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@ogrisel ogrisel left a comment

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LGTM. @NicolasHug are you fine with merging without your suggestion?

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yes

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ogrisel commented Jan 30, 2020

I saw #16322 (comment) just after my comment above.

As you wish. +0 for the None weight fast path option.

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As you wish. +0 for the None weight fast path option.

let's ignore that for this PR

@ogrisel ogrisel merged commit 5ea6a26 into scikit-learn:master Jan 30, 2020
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ogrisel commented Jan 30, 2020

Merged then! Thank you very much @Batalex.

@Batalex Batalex deleted the refact/check-isotonic branch January 30, 2020 16:21
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+0 for the None weight fast path option.

It's not applicable here anyway because the fast way isn't implemented for IsotonicRegeression

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Use _check_sample_weight to consistently validate sample_weight
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