TST check equivalence sample_weight in CalibratedClassifierCV #21179
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Since this PR is reusing some work from #20638 please amend a commit of this PR to mark co-authorship with The following should do: And type as the commit message: |
ogrisel
reviewed
Sep 29, 2021
ogrisel
reviewed
Sep 29, 2021
| "zero sample_weight is not equivalent to removing samples" | ||
| "Due to the cross-validation and sample ordering, removing a sample" | ||
| " is not strictly equal to putting is weight to zero. Specific unit" | ||
| " tests are added for CalibratedClassifierCV specifically." |
ogrisel
reviewed
Sep 29, 2021
| y_pred_with_weights = calibrated_clf_with_weights.predict_proba(X) | ||
| y_pred_without_weights = calibrated_clf_without_weights.predict_proba(X) | ||
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| assert_allclose(y_pred_with_weights, y_pred_without_weights) |
ogrisel
approved these changes
Sep 29, 2021
Co-authored-by: JulienB-78 <jbohne78-github@yahoo.fr>
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ogrisel
reviewed
Sep 29, 2021
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
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@rth or @lorentzenchr as sample_weight fans, you might be interested in reviewing this one. |
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@agramfort as well :) |
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…-learn#21179) Co-authored-by: JulienB-78 <jbohne78-github@yahoo.fr> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
glemaitre
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Co-authored-by: JulienB-78 <jbohne78-github@yahoo.fr> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
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…-learn#21179) Co-authored-by: JulienB-78 <jbohne78-github@yahoo.fr> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
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related to #21143
This PR looks at the impact of
sample_weightinCalibratedClassifierCV.