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jeremiedbb
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thanks for the PR @Connerrrrr. Here are a few comments.
(also synchronizing with main will fix the failing CI job)
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@jeremiedbb Thanks for the comment! They are all resolved now. |
jeremiedbb
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LGTM. Thanks @Connerrrrr !
ogrisel
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LGTM as well. Thanks for the fix!
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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 #16924
What does this implement/fix? Explain your changes.
The original MCC function included the case of confusion matrix has all zeros but for one column. However, the original solution did not expect the warning message would pop up, even the return value is correct.
According to Jurman, Riccadonna, Furlanello, (2012). A Comparison of MCC and CEN Error Measures in MultiClass Prediction
and Wikipedia of Matthews Correlation Coefficient,
the fix is checking whenever there is only a column or a row in the confusion matrix that is non-zero, the MCC automatically set to 0.