[MRG + 1] Fix docstring typo #7844
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@tguillemot Fine by you? |
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LGTM. |
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* tag '0.18.1': (144 commits) skip tree-test on 32bit do the warning test as we do it in other places. Replase assert_equal by assert_almost_equal in cosine test version bump 0.18.1 fix merge conflict mess in whatsnew add the python2.6 warning to 0.18.1 fix learning_curve test that I messed up in cherry-picking the "reentrant cv" PR. sync whatsnew with master [MRG] TST Ensure __dict__ is unmodified by predict, transform, etc (scikit-learn#7553) FIX scikit-learn#6420: Cloning decision tree estimators breaks criterion objects (scikit-learn#7680) Add whats new entry for scikit-learn#6282 (scikit-learn#7629) [MGR + 2] fix selectFdr bug (scikit-learn#7490) fixed whatsnew cherry-pick mess (somewhat) [MRG + 2] FIX LogisticRegressionCV to correctly handle string labels (scikit-learn#5874) [MRG + 2] Fixed parameter setting in SelectFromModel (scikit-learn#7764) [MRG+2] DOC adding separate `fit()` methods (and docstrings) for DecisionTreeClassifier and DecisionTreeRegressor (scikit-learn#7824) Fix docstring typo (scikit-learn#7844) n_features --> n_components [MRG + 1] DOC adding :user: role to whats_new (scikit-learn#7818) [MRG+1] label binarizer not used consistently in CalibratedClassifierCV (scikit-learn#7799) DOC : fix docstring of AIC/BIC in GMM ...
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* releases: (144 commits) skip tree-test on 32bit do the warning test as we do it in other places. Replase assert_equal by assert_almost_equal in cosine test version bump 0.18.1 fix merge conflict mess in whatsnew add the python2.6 warning to 0.18.1 fix learning_curve test that I messed up in cherry-picking the "reentrant cv" PR. sync whatsnew with master [MRG] TST Ensure __dict__ is unmodified by predict, transform, etc (scikit-learn#7553) FIX scikit-learn#6420: Cloning decision tree estimators breaks criterion objects (scikit-learn#7680) Add whats new entry for scikit-learn#6282 (scikit-learn#7629) [MGR + 2] fix selectFdr bug (scikit-learn#7490) fixed whatsnew cherry-pick mess (somewhat) [MRG + 2] FIX LogisticRegressionCV to correctly handle string labels (scikit-learn#5874) [MRG + 2] Fixed parameter setting in SelectFromModel (scikit-learn#7764) [MRG+2] DOC adding separate `fit()` methods (and docstrings) for DecisionTreeClassifier and DecisionTreeRegressor (scikit-learn#7824) Fix docstring typo (scikit-learn#7844) n_features --> n_components [MRG + 1] DOC adding :user: role to whats_new (scikit-learn#7818) [MRG+1] label binarizer not used consistently in CalibratedClassifierCV (scikit-learn#7799) DOC : fix docstring of AIC/BIC in GMM ... Conflicts: removed sklearn/externals/joblib/__init__.py sklearn/externals/joblib/_parallel_backends.py sklearn/externals/joblib/testing.py
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* dfsg: (144 commits) skip tree-test on 32bit do the warning test as we do it in other places. Replase assert_equal by assert_almost_equal in cosine test version bump 0.18.1 fix merge conflict mess in whatsnew add the python2.6 warning to 0.18.1 fix learning_curve test that I messed up in cherry-picking the "reentrant cv" PR. sync whatsnew with master [MRG] TST Ensure __dict__ is unmodified by predict, transform, etc (scikit-learn#7553) FIX scikit-learn#6420: Cloning decision tree estimators breaks criterion objects (scikit-learn#7680) Add whats new entry for scikit-learn#6282 (scikit-learn#7629) [MGR + 2] fix selectFdr bug (scikit-learn#7490) fixed whatsnew cherry-pick mess (somewhat) [MRG + 2] FIX LogisticRegressionCV to correctly handle string labels (scikit-learn#5874) [MRG + 2] Fixed parameter setting in SelectFromModel (scikit-learn#7764) [MRG+2] DOC adding separate `fit()` methods (and docstrings) for DecisionTreeClassifier and DecisionTreeRegressor (scikit-learn#7824) Fix docstring typo (scikit-learn#7844) n_features --> n_components [MRG + 1] DOC adding :user: role to whats_new (scikit-learn#7818) [MRG+1] label binarizer not used consistently in CalibratedClassifierCV (scikit-learn#7799) DOC : fix docstring of AIC/BIC in GMM ...
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Reference Issue
What does this implement/fix? Explain your changes.
Fix a docstring typo for the resp argument of
gaussian_mixture. _estimate_gaussian_parameters()where shape was given as(n_samples, n_features)but should be(n_samples, n_components).Any other comments?