Complete deprecations finishing in 0.21 #11992

jnothman · 2018-09-04T00:01:42Z

$ git grep -w "0\.21" 'sklearn/*.py'
sklearn/cluster/hierarchical.py:                      "will be removed in 0.21", DeprecationWarning)
sklearn/covariance/graph_lasso_.py:                "will be removed in 0.21. Use ``grid_scores_`` instead")
sklearn/covariance/tests/test_graph_lasso.py:                    "0.19 and will be removed in 0.21. Use "
sklearn/covariance/tests/test_graphical_lasso.py:                    "0.19 and will be removed in 0.21. Use "
sklearn/datasets/mlcomp.py:            "in version 0.19 and will be removed in 0.21.")
sklearn/decomposition/fastica_.py:               This parameter will be removed in 0.21.
sklearn/decomposition/fastica_.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/decomposition/online_lda.py:        be removed in version 0.21.
sklearn/decomposition/online_lda.py:                          "version 0.19 and will be removed in 0.21",
sklearn/decomposition/online_lda.py:                          "argument will be removed in 0.21.",
sklearn/decomposition/sparse_pca.py:               This parameter will be removed in 0.21.
sklearn/decomposition/sparse_pca.py:                          "deprecated since 0.19 and will be removed in 0.21. "
sklearn/discriminant_analysis.py:                " 0.19 and will be removed in 0.21. Use "
sklearn/discriminant_analysis.py:                          " in version 0.19 and will be removed in 0.21.",
sklearn/ensemble/forest.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/forest.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/forest.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/forest.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/forest.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/gradient_boosting.py:                "will be removed in 0.21.")
sklearn/ensemble/gradient_boosting.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/gradient_boosting.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/ensemble/tests/test_voting_classifier.py:                "changed to True in 0.21. "
sklearn/ensemble/voting_classifier.py:                              "changed to True in 0.21. "
sklearn/feature_extraction/hashing.py:            This option will be removed in 0.21.
sklearn/feature_extraction/hashing.py:                          " in version 0.21.", DeprecationWarning)
sklearn/feature_extraction/text.py:            This option will be removed in 0.21.
sklearn/gaussian_process/gpr.py:                "will be removed in 0.21.")
sklearn/gaussian_process/gpr.py:                "will be removed in 0.21.")
sklearn/kernel_approximation.py:                    " raise an error in 0.21, as they are ignored. Use "
sklearn/linear_model/least_angle.py:                "will be removed in 0.21. See ``alpha_`` instead")
sklearn/linear_model/passive_aggressive.py:        Defaults to 5. Defaults to 1000 from 0.21, or if tol is not None.
sklearn/linear_model/passive_aggressive.py:        Defaults to 1e-3 from 0.21.
sklearn/linear_model/passive_aggressive.py:        Defaults to None. Deprecated, will be removed in 0.21.
sklearn/linear_model/passive_aggressive.py:        Defaults to 5. Defaults to 1000 from 0.21, or if tol is not None.
sklearn/linear_model/passive_aggressive.py:        Defaults to 1e-3 from 0.21.
sklearn/linear_model/passive_aggressive.py:        Defaults to None. Deprecated, will be removed in 0.21.
sklearn/linear_model/perceptron.py:        Defaults to 5. Defaults to 1000 from 0.21, or if tol is not None.
sklearn/linear_model/perceptron.py:        Defaults to 1e-3 from 0.21.
sklearn/linear_model/perceptron.py:        Defaults to None. Deprecated, will be removed in 0.21.
sklearn/linear_model/randomized_l1.py:            " and will be removed in 0.21.")
sklearn/linear_model/randomized_l1.py:            " and will be removed in 0.21.")
sklearn/linear_model/randomized_l1.py:            " and will be removed in 0.21.")
sklearn/linear_model/randomized_l1.py:            " and will be removed in 0.21.")
sklearn/linear_model/stochastic_gradient.py:                          " removed in 0.21. Use max_iter and tol instead.",
sklearn/linear_model/stochastic_gradient.py:                    "From 0.21, default max_iter will be 1000, and"
sklearn/linear_model/stochastic_gradient.py:                "will be removed in 0.21. Use ``loss_function_`` instead")
sklearn/linear_model/stochastic_gradient.py:        Defaults to 5. Defaults to 1000 from 0.21, or if tol is not None.
sklearn/linear_model/stochastic_gradient.py:        Defaults to 1e-3 from 0.21.
sklearn/linear_model/stochastic_gradient.py:        Defaults to None. Deprecated, will be removed in 0.21.
sklearn/linear_model/stochastic_gradient.py:        Defaults to 5. Defaults to 1000 from 0.21, or if tol is not None.
sklearn/linear_model/stochastic_gradient.py:        Defaults to 1e-3 from 0.21.
sklearn/linear_model/stochastic_gradient.py:        Defaults to None. Deprecated, will be removed in 0.21.
sklearn/linear_model/tests/test_randomized_l1.py:                         "deprecated in 0.19 and will be removed in 0.21.",
sklearn/linear_model/tests/test_randomized_l1.py:                         "deprecated in 0.19 and will be removed in 0.21.",
sklearn/linear_model/tests/test_randomized_l1.py:                         "deprecated in 0.19 and will be removed in 0.21.",
sklearn/linear_model/tests/test_sgd.py:    # Test that warnings are raised. Will be removed in 0.21
sklearn/manifold/t_sne.py:                "will be removed in 0.21. Use ``n_iter_`` instead")
sklearn/metrics/pairwise.py:                      '0.21 of scikit-learn', DeprecationWarning)
sklearn/model_selection/_search.py:                          'in version 0.21. Pass fit parameters to the '
sklearn/model_selection/_search.py:        # TODO: replace by a dict in 0.21
sklearn/model_selection/_search.py:                            'any more in 0.21. If you need training scores, '
sklearn/model_selection/_search.py:           0.19 and will be removed in version 0.21. Pass fit parameters to
sklearn/model_selection/_search.py:        will change to False in version 0.21, to correspond to the standard
sklearn/model_selection/_search.py:        That default will be changed to ``False`` in 0.21.
sklearn/model_selection/_search.py:           0.19 and will be removed in version 0.21. Pass fit parameters to
sklearn/model_selection/_search.py:        will change to False in version 0.21, to correspond to the standard
sklearn/model_selection/_search.py:        That default will be changed to ``False`` in 0.21.
sklearn/model_selection/_split.py:        The default will change in version 0.21. It will remain 0.1 only
sklearn/model_selection/_split.py:        The default will change in version 0.21. It will remain 0.2 only
sklearn/model_selection/_split.py:                warnings.warn("From version 0.21, test_size will always "
sklearn/model_selection/_split.py:        The default will change in version 0.21. It will remain 0.1 only
sklearn/model_selection/_split.py:            warnings.warn("From version 0.21, test_size will always "
sklearn/model_selection/_split.py:        The default will change in version 0.21. It will remain 0.25 only
sklearn/model_selection/_split.py:            warnings.warn("From version 0.21, test_size will always "
sklearn/model_selection/_validation.py:        That default will be changed to ``False`` in 0.21.
sklearn/model_selection/_validation.py:    # TODO: replace by a dict in 0.21
sklearn/model_selection/_validation.py:                    'any more in 0.21. If you need training scores, '
sklearn/model_selection/tests/test_search.py:    # Test that warnings are raised. Will be removed in 0.21
sklearn/model_selection/tests/test_search.py:            'any more in 0.21. If you need training scores, '
sklearn/model_selection/tests/test_validation.py:    # Test that warnings are raised. Will be removed in 0.21
sklearn/model_selection/tests/test_validation.py:        'any more in 0.21. If you need training scores, '
sklearn/neighbors/approximate.py:                      "in 0.19. It will be removed in version 0.21.",
sklearn/neighbors/tests/test_approximate.py:                         "in version 0.21.", LSHForest)
sklearn/preprocessing/__init__.py:# stub, remove in version 0.21
sklearn/preprocessing/_function_transformer.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/preprocessing/_function_transformer.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/preprocessing/_function_transformer.py:                          "will be removed in 0.21", DeprecationWarning)
sklearn/preprocessing/data.py:               This parameter will be removed in 0.21.
sklearn/preprocessing/data.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/preprocessing/data.py:               This parameter will be removed in 0.21.
sklearn/preprocessing/data.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/preprocessing/data.py:               This parameter will be removed in 0.21.
sklearn/preprocessing/data.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/preprocessing/data.py:               This parameter will be removed in 0.21.
sklearn/preprocessing/data.py:                          "deprecated since 0.19 and will be removed in 0.21",
sklearn/preprocessing/data.py:    This stub will be removed in version 0.21.
sklearn/preprocessing/data.py:            "This stub will be removed in version 0.21.")
sklearn/semi_supervised/label_propagation.py:            This parameter will be removed in 0.21.
sklearn/semi_supervised/label_propagation.py:                "alpha is deprecated since 0.19 and will be removed in 0.21.",
sklearn/tests/test_discriminant_analysis.py:                         "removed in 0.21.", clf.fit, X, y)
sklearn/tests/test_discriminant_analysis.py:                         "in 0.21. Use ``covariance_`` instead", getattr, clf,
sklearn/tree/tree.py:                          " will be removed in version 0.21. "
sklearn/tree/tree.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/tree/tree.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/tree/tree.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/tree/tree.py:           ``min_impurity_decrease`` in 0.19 and will be removed in 0.21.
sklearn/utils/arpack.py:# Remove this module in version 0.21
sklearn/utils/arpack.py:            "will be removed in 0.21. Use scipy.sparse.linalg.eigs instead.")
sklearn/utils/arpack.py:            "will be removed in 0.21. Use scipy.sparse.linalg.eigsh instead.")
sklearn/utils/arpack.py:            "will be removed in 0.21. Use scipy.sparse.linalg.svds instead.")
sklearn/utils/estimator_checks.py:                # To remove in 0.21, when they get their future default values
sklearn/utils/extmath.py:            "and will be removed in 0.21. Use scipy.linalg.norm instead.")
sklearn/utils/extmath.py:            "and will be removed in 0.21. Use the equivalent np.dot instead.")
sklearn/utils/extmath.py:            "and will be removed in 0.21. Use scipy.misc.logsumexp instead.")
sklearn/utils/extmath.py:            "and will be removed in 0.21. Use scipy.linalg.pinvh instead.")
sklearn/utils/graph.py:            "version 0.19 and will be removed in 0.21. Use "
sklearn/utils/graph.py:            "0.19 and will be removed in 0.21. Use "
sklearn/utils/random.py:            "and will be removed in 0.21. Use np.random.choice or "
sklearn/utils/sparsetools/__init__.py:# Remove in version 0.21
sklearn/utils/sparsetools/__init__.py:            "version 0.19 and will be removed in 0.21. Use "
sklearn/utils/sparsetools/setup.py:# Remove in version 0.21
sklearn/utils/stats.py:# Remove in sklearn 0.21
sklearn/utils/stats.py:            "will be removed in 0.21. Use scipy.stats.rankdata instead.")
sklearn/utils/tests/test_extmath.py:@ignore_warnings  # Test deprecated backport to be removed in 0.21
sklearn/utils/tests/test_extmath.py:@ignore_warnings  # extmath.norm is deprecated to be removed in 0.21
sklearn/utils/tests/test_stats.py:    # Test deprecated backport to be removed in 0.21
sklearn/utils/tests/test_utils.py:@ignore_warnings  # Test deprecated backport to be removed in 0.21
sklearn/utils/tests/test_utils.py:@ignore_warnings  # Test deprecated backport to be removed in 0.21
sklearn/utils/tests/test_utils.py:@ignore_warnings  # Test deprecated backport to be removed in 0.21
sklearn/utils/tests/test_utils.py:@ignore_warnings  # Test deprecated backport to be removed in 0.21
sklearn/utils/validation.py:           deprecated in version 0.19 "and will be removed in 0.21. Use
sklearn/utils/validation.py:            "and will be removed in 0.21. Use 'accept_sparse=False' "
sklearn/utils/validation.py:           deprecated in version 0.19 "and will be removed in 0.21. Use

The text was updated successfully, but these errors were encountered:

rth · 2018-09-04T06:45:15Z

Same comment as in #11991 (comment) ...

amueller · 2018-09-06T19:40:13Z

I agree, let's wait for the final release, but then hurray!

amueller · 2018-09-06T19:40:33Z

(if I have time I'll do this just for the satisfaction of deleting so much code, as usual ;)

jnothman · 2018-09-06T23:47:22Z

Yes, but to help it get merged in a reasonable time frame, maybe split up the pr this time.

amueller · 2018-10-01T20:39:45Z

hopefully it will be smaller this time around...

amueller · 2018-10-01T21:31:33Z

so I'm going through most of these. I think the SGDClassifier max_int/n_iter/tol thing maybe should go in its own PR. possibly the train_size/test_size thing, too?

amueller · 2018-10-01T21:52:44Z

I started on everything but the train_size/test_size thing.

amueller · 2018-10-01T21:53:41Z

Maybe a reviewer can start with #12238 which is the biggest but should be a straight-forward removal of lots of stuff.

amueller · 2018-10-01T21:53:53Z

I can split up #12238 further if you like, though.

amueller · 2018-10-01T22:24:53Z

a lot of the FeatureHasher tests assume the existence of non_negative. I'm not sure how to rewrite these.

Part of #11992. These were all the things that seemed pretty straight-forward. It's actually a bit bulky but should still be easy to review, hopefully.

adrinjalali · 2019-04-29T14:24:07Z

I think this is done.

jnothman added help wanted Easy Well-defined and straightforward way to resolve Moderate Anything that requires some knowledge of conventions and best practices and removed Easy Well-defined and straightforward way to resolve labels Sep 4, 2018

This was referenced Oct 1, 2018

MNT simple deprecations and removals for 0.21 #12238

Merged

Deprecations 0.21 sgd tol #12239

Closed

trees and forests min_impurity_split deprecation #12240

Closed

[MRG + 1] return_train_score deprecation #12241

Merged

amueller mentioned this issue Oct 2, 2018

MNT complete VotingClassifier flatten_transform deprecation #12252

Merged

amueller added a commit that referenced this issue Oct 11, 2018

MNT simple deprecations and removals for 0.21 (#12238)

0f94f29

Part of #11992. These were all the things that seemed pretty straight-forward. It's actually a bit bulky but should still be easy to review, hopefully.

adrinjalali added this to the 0.21 milestone Apr 29, 2019

jnothman closed this as completed Apr 29, 2019

rth mentioned this issue May 31, 2019

solve underflow errors by changing utils/extmath.py -> logsumexp() #6205

Closed

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Complete deprecations finishing in 0.21 #11992

Complete deprecations finishing in 0.21 #11992

jnothman commented Sep 4, 2018 •

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rth commented Sep 4, 2018

amueller commented Sep 6, 2018

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amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

adrinjalali commented Apr 29, 2019

Complete deprecations finishing in 0.21 #11992

Complete deprecations finishing in 0.21 #11992

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jnothman commented Sep 4, 2018 • edited Loading

rth commented Sep 4, 2018

amueller commented Sep 6, 2018

amueller commented Sep 6, 2018

jnothman commented Sep 6, 2018 via email

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

amueller commented Oct 1, 2018

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amueller commented Oct 1, 2018

adrinjalali commented Apr 29, 2019

jnothman commented Sep 4, 2018 •

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