FIX Fix error when using Calibrated with Voting#20087
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thomasjpfan merged 1 commit intoscikit-learn:mainfrom Jun 4, 2021
cfauchereau:calibrate_and_voting
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FIX Fix error when using Calibrated with Voting#20087thomasjpfan merged 1 commit intoscikit-learn:mainfrom cfauchereau:calibrate_and_voting
thomasjpfan merged 1 commit intoscikit-learn:mainfrom
cfauchereau:calibrate_and_voting
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thomasjpfan
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Thank you for working on this issue @Clement-F !
sklearn/calibration.py
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| elif method_name == 'predict_proba' or method_name == '_predict_proba': | ||
| # The `_predict_proba` option is needed for `VotingClassifier` |
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I do not think special casing VotingClassifier is great. I think it would be better to get _get_prediction_method to return a tuple (callable, method_name) and then use the method_name here.
(_get_prediction_method is always called before _compute_predictions)
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I agree. I have updated the code.
ogrisel
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LGTM, thanks for the fix. Just a few minor suggestions:
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* TST enable test docstring params for feature extraction module (scikit-learn#20188) * DOC fix a reference in sklearn.ensemble.GradientBoostingRegressor (scikit-learn#20198) * FIX mcc zero divsion (scikit-learn#19977) * TST Add TransformedTargetRegressor to test_meta_estimators_delegate_data_validation (scikit-learn#20175) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * TST enable n_feature_in_ test for feature_extraction module * FIX Uses points instead of pixels in plot_tree (scikit-learn#20023) * MNT n_features_in through the multiclass module (scikit-learn#20193) * CI Removes python 3.6 builds from wheel building (scikit-learn#20184) * FIX Fix typo in error message in `fetch_openml` (scikit-learn#20201) * FIX Fix error when using Calibrated with Voting (scikit-learn#20087) * FIX Fix RandomForestRegressor doesn't accept max_samples=1.0 (scikit-learn#20159) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * ENH Adds Poisson criterion in RandomForestRegressor (scikit-learn#19836) Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com> Co-authored-by: Alihan Zihna <alihanz@gmail.com> Co-authored-by: Alihan Zihna <a.zihna@ckhgbdp.onmicrosoft.com> Co-authored-by: Chiara Marmo <cmarmo@users.noreply.github.com> Co-authored-by: Olivier Grisel <olivier.grisel@gmail.com> Co-authored-by: naozin555 <37050583+naozin555@users.noreply.github.com> Co-authored-by: Venkatachalam N <venky.yuvy@gmail.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * TST Replace assert_warns from decomposition/tests (scikit-learn#20214) * TST check n_features_in_ in pipeline module (scikit-learn#20192) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Olivier Grisel <olivier.grisel@gmail.com> * Allow `n_knots=None` if knots are explicitly specified in `SplineTransformer` (scikit-learn#20191) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * FIX make check_complex_data deterministic (scikit-learn#20221) * TST test_fit_docstring_attributes include properties (scikit-learn#20190) * FIX Uses the color max for colormap in ConfusionMatrixDisplay (scikit-learn#19784) * STY Changing .format method to f-string formatting (scikit-learn#20215) * CI Adds permissions for label action Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: tsuga <2888173+tsuga@users.noreply.github.com> Co-authored-by: Conner Shen <connershen98@hotmail.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: mlondschien <61679398+mlondschien@users.noreply.github.com> Co-authored-by: Clément Fauchereau <clement.fauchereau@ensta-bretagne.org> Co-authored-by: murata-yu <67666318+murata-yu@users.noreply.github.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Brian Sun <52805678+bsun94@users.noreply.github.com> Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com> Co-authored-by: Alihan Zihna <alihanz@gmail.com> Co-authored-by: Alihan Zihna <a.zihna@ckhgbdp.onmicrosoft.com> Co-authored-by: Chiara Marmo <cmarmo@users.noreply.github.com> Co-authored-by: Olivier Grisel <olivier.grisel@gmail.com> Co-authored-by: naozin555 <37050583+naozin555@users.noreply.github.com> Co-authored-by: Venkatachalam N <venky.yuvy@gmail.com> Co-authored-by: Nanshan Li <nanshanli@dsaid.gov.sg> Co-authored-by: solosilence <abhishekkr23rs@gmail.com>
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Reference Issues/PRs
Fixes #20053
What does this implement/fix? Explain your changes.
The commit #17856 changed the way
CalibratedClassifierCVinternally works. Due to weird implementation ofVotingClassifier.predict_proba, it broke the compatibility whenVotingClassifieris used asbase_estimatorinCalibratedClassifier.This is a simple fix to restore compatibility.
Any other comments?
The real issue is the way
VotingClassifier.predict_probais implemented. However, it seems to me that it can't be resolved without breaking changes.The issue is that
predict_probais not a method but an attribute which holds another method. The goal of this trick was to do polymorphism and implementpredict_probaonly whenvoting="soft"using a getter.I think
VotingClassifiershould be an abstract class and we should implementSoftVotingClassifierandHardVotingClassifiersince they don't implement the same methods. It is however a big API change.It would be simpler to only raise an error if
voting="hard"but if I understand correctly it is assumed that ifpredict_probaexists then it must work. It would therefore leads to other incompatibilities.I am not familiar enough with the code base to know how it is usually dealt with. Anyway, I think it needs further discussion.