[MRG] Release 0.21.3 #14188

jnothman · 2019-06-25T23:44:37Z

To be merged without squashing.

I thought we should consider if 0.21.3 should be released at some point soon (early July). It's one month since 0.21.2 was released. This branch currently just includes https://github.com/scikit-learn/scikit-learn/milestone/30?closed=1 and https://github.com/scikit-learn/scikit-learn/milestone/34?closed=1. We should review documentation commits that should also be included.

The initial commit selection is:

drop 0b3aa5e466 DOC bump version
drop 10249939e5 DOC move 0.20 to previous releases
drop e7bd8a33e5 FIX Optics paper typo which resulted in undersized clusters (#13750)
drop 384c8ad3d3 ENH add a break_ties parameter to SVC and NuSVC (#12557)
drop 13981bdce9 STY Remove variable renaming (#13731)
drop 19192c0427 MAINT Replace manual checks with `check_is_fitted`  (#13013)
drop 905dedc635 DEP remove random_state from OneClassSVM (#13802)
drop 28480f4cb2 DEP change the default of gamma in SVM (#13801)
drop d0a94fea74 DEP remove graph lasso (#13795)
drop 7896b21562 MNT change default of solver in LogisiticRegression (#13805)
drop 6525a39dd6 MNT Remove Imputer in preprocessing (#13796)
drop 43f85020c5 DEP remove correlation and regression models from GaussianProcess (#13819)
drop 2b7a69baca DEP remove the batch_size parameter from pariwise_distance_argmin (#13822)
drop 53624e8c26 DEP remove public function download_20newsgroups (#13829)
drop 9631a67388 DEP remove scale_face function from lfw (#13830)
drop 777f91f114 [MRG] DEP Removed the reorder parameter from the auc function (#13827)
drop 7166ae8ece MNT Updated adjusted_mutual_info_score and normalized_mutual_info_score default to 'arithmetic' (#13814)
drop 91e019df5e DEP remove precomputed parameter in t_sne.trustworthiness (#13820)
drop 69eb4d4678 [MRG] DEP change default and deprecate iid in SearchCV (#13834)
drop c7566ea232 disallow input as sparse matrix in affinity propagation function, Aff… (#13828)
drop 95339a677e [MRG] DEP remove pooling_func in AgglomerativeClustering (#13821)
drop 7fdac52c19 MNT Remove backward compatibility of param order in make_column_transformer (#13831)
drop 8a8e21b2a3 MNT Change the default value of n_estimators in forests (#13803)
drop 83656484a8 MNT Remove raises and with_setup requiring nose (#13842)
drop da9e680996 DOC fix the docstring of AMI MNI regarding new default (#13837)
drop eec7614a1f Small fixes to maintainer commands
drop b243c6aa43 DEP change default of contamination in LOF (#13815)
drop 75967ef20e DEP remove deprecated parameters in EllipticEnvelope (#13818)
drop 11de9d60f2 Updating MissingIndicator User Guide section (#13849)
drop 4e65827b5c [MRG] RidgeCV minor refactor to improve readability (#13832)
drop 5d240c6a0b MAINT Fixes coverage reporting on pylatest_conda (#13895)
drop af4247b152 DEP remove utilities related to mldata (#13798)
drop 0bfa52dad7 DEP Change default of error_score in cross-validation (#13840)
drop 911792b008 ENH Avoid calling _encode_check_unknown() twice in BaseEncoder.transform (#13810)
drop 57c04f4e8d ENH Allows setting of initial hyperparameters for BayesianRidge (#13618)
drop 778b11904e [MRG] DEP remove threshold_, change contamination, deprecate behaviour in iforest (#13811)
drop c28ef9ef2a DEP change the default of multi_class to 'auto' in logistic regression (#13807)
drop e0532cdea5 MAINT increase numerical gradient check tolerance to make the test stable (#13885)
drop 8f378ca684 DOC Fix bracket typo in linear_model.rst (#13932)
drop e747376eef [MRG] MAINT Fixes apt by removing the ubuntu-toolchain-r/test repo (#13934)
drop 22b0eabfd0 DOC add 0.21.3 entry
pick f3a6a1a6c8 TST avoid nose collecting train_test_split as a test (#13951)
drop db48ebce60 ENH add n_components kwarg to SpectralClustering. See #13698 (#13726)
pick fa383a4aca FIX plot_tree now displays correct criterion (#13947)
drop cebefd4f01 DOC adds instructions for building on FreeBSD (#13953)
drop 69dd9a54e2 DOC correct headline level in contributor docs (#13959)
drop 57726672b5 CLN Remove parent negative loss calculation from for loop to improve performance (#13955)
drop 2a7194de7a FIX Bin training and validation data separately in GBDTs (#13933)
drop be03467b9c FIX Changed VarianceThreshold behaviour when threshold is zero. See #13691 (#13704)
drop 9f7e8671dc PERF Free problem and param sooner in liblinear.train_wrap
drop f283ed6b40 CLN Removed max_bins from splitter in GBDT (#13927)
drop 54e6c720de CLN Refactors code (#13966)
pick 7ea7284f22 MAINT: use explicit value of n_jobs to avoid hangs on Windows (#13970)
drop b271e20570 DEP remove positive parameter for lars solver (#13863)
drop a98db9a4d6 DEP change default and deprecate normalize_components in SparsePCA (#13838)
drop 9ee164baa3 [MRG] DEP remove legacy mode from OneHotEncoder (#13855)
drop 9328581ec5 FIX use CD solver in face decomposition to use postive parameter (#13975)
drop 9adba491a2 [MRG] DEP change the default of cv and n_splits (#13839)
drop 7ee46f1717 FIX Lazy cython import for pytest to work without cython
drop 3ed200292f Added matplotlib to show_versions() (#13983)
drop 233fd6df32 DOC add doc example to OneClassSVM
drop ccd6399cad CLN GBDTs: don't split on last bin (explicitly) (#13919)
drop 896a76eb22 [MRG][DOC] Fix inconsistencies in clustering doc. (#13946)
drop e871a56d44 DOC Fixed documentation typos (#13993)
drop 5e0d1a1f04 DOC Fix typo: omit comma (#13999)
drop 9661a64fae ENH Avoid uncessary copies in sklearn.preprocessing (#13987)
drop 2e7e06b78f [MRG] Doctest with print change only adjusts default options for doctest (#13991)
pick 162216af26 MAINT: test_encoder_dtypes_pandas reads expected dtype from DF (#13997)
drop 15b54340ee [MRG] CLN Only one function for parallel predict (#14003)
drop ccd3331f7e MNT remove unused imports (#14021)
drop 6675c9e342 MAINT pass n_samples instead of sample_indices in GBDT (#14017)
drop ec35ed226c EHN Add function score_samples to Pipeline (#13806)
drop 2b571c039d MNT better message for pillow import error (#14027)
drop abf7721904 TST fix a part of Gradient Boosting test which wasn't running (#14032)
drop 69dbdf4f9b MNT DOC don't warn if a ref with single backtick is not found (#14040)
drop 0f801d7ba8 DOC link set_config and config_context in docstrings (#14030)
pick a80d679ff7 MNT DOC fix some sphinx warnings on what's new files (#14049)
drop b3d716c924 DOC Fixes default value for eta0 in SGDRegressor (#14047)
drop 8342548ae1 EXA Remove useless sections in omp example (#14019)
drop 61f6f5bcd1 TST add test to check that all ridge solver give the same results (#13914)
drop c315bf9314 MNT Ignore setup.py in the coverage report (#14052)
drop 9d7b804603 MAINT: adjustments to test_logistic.py::test_dtype_match (#13645)
drop d84a8d17af ENH Binary only estimator checks for classification (#13875)
drop 4c58057dda DOC Add what's new for binary only estimator checks (#13875)
drop 9c732e15a8 DOC Fix typo in manifold documentation (#14073)
drop 227ebc4815 DOC fix the default value of learning_rate in docstring of HistGBC. (#14072)
drop e669a89aa4 CLN Removed some unused imports (#14074)
drop 05b12cfcfd PERF Shrink arrays to size in liblinear helper dense_to_sparse (#14026)
drop 2fc3a85b3f MAINT Use isinstance(x, numbers.Integral) to check for integer dtype (#14004)
drop 73caac258c MAINT Fixes lgtm errors (#14041)
drop 50425e1dfe MAINT Remove sudo tag in travis (#14050)
drop d91b0f324b MNT refactor naive Bayes tests (#14064)
pick 8fe89ea524 FIX wrong usage and occurrence of string tag (#14043)
drop fd1d210362 DOC add kcachegrind visualization docs (#8016)
drop 4a6264db68 TST add test for pipeline in partial dependence (#14079)
drop 76ce7c5b63 DEP change default validate in FunctionTransformer to False(#13817)
drop a5743ed36f TST add test for LAD-loss and quantile loss equivalence (old GBDT code) (#14086)
pick b580ad5dfd BUG Fix zero division error in GBDTs (#14024)
drop bec83089f7 MAINT Uses pytest-xdist to parallelize tests (#13041)
drop e2a69b7376 DOC use train/test split in GaussianNB example (#14080)
drop df7dd83911 ENH allow sparse input to incremental PCA (#13960)
drop 3ec339a58f Added colorblind compatibility (#14091)
pick 36b688eb04 [MRG] fix refit=False error in LogisticRegressionCV (#14087)
drop b28aadf6ef Added fit and score times for learning_curve (#13938)
drop eed5cba610 TST Check that estimators are not cloned during pipeline construction (#7633)
pick cb12053c57 DOC Make parameter, etc listings use small screen width better (#9503)
drop 6ab8c86c38 [MRG] DOC DOC sklearn.manifold.t_sne.trustworthiness added to classes.rst (#9747)
drop 0eedf99eee MAINT Don't use clean_warnings_registry in tests (#14085)
drop 120009b12a DOC fix user guide for learning_curve (#14099)
drop b7c4163690 FIX Fix off-by-one error in liblinear helper dense_to_sparse (#14103)
pick e2b6bff0ac BUG Fixes export_text with single feature (#14053)
drop 1015caf54d MAINT Remove imports from sklearn.utils._joblib (#13676)
drop 7ce8b21cd1 PERF Don't allocate space for bias element if there isn't one (#14108)
pick 197f448eed [MRG] Fix NCA parameter type check (#14092)
drop 4a325353ef MNT Fix some typos in README (#14122)
drop f9f8974216 DOC updated class_weight explanation in glossary (#14121)
drop 801cca8e73 MNT fix suppressing matplotlib warning issue while making docs (#14115)
drop b3030f046f minor fix in gaussian_mixture.py (#14120)
drop 0c110701f9 TST Fixed typo in test_column_transformer (#14128)
drop 8632775c23 FIX Fix memory leak in liblinear helper csr_to_sparse error path (#14118)
drop 842df6f60e MAINT Faster linear_model tests (#14105)
drop ab4b4ec5eb DOC add clarification on random forest default params (#13248)
pick 6b811ac2c3 DOC add missing what's new to pr 14092 (#14133)
drop 214def06a3 DOC Contributing guide update (#13961)
drop cf2e60bc1b MAINT Simplify arguments to csr_set_problem and csr_to_sparse (#14135)
drop c0d77d4d37 DOC: document resulting NaN in SimpleImputer.statistics_ (#14129)
drop da96da96f0 EHN Add warm_start parameter to HistGradientBoosting (#14012)
drop 3d997697fd [MRG] Error for cosine affinity when zero vectors present (#7943)
drop e94f5de906 FIX remove action of normalize_components in SparsePCA (#14134)
drop ee8bdd0b61 ENH Add joblib to the list of dependencies in show_versions (#14141)
drop 8681ece373 ENH Fix unfriendly error message for documentation checks (#11967)
drop 5674122c97 MAINT More test runtime optimizations (#14136)
drop 5b8b6277a3 DOC fixing the missing fetch upstream in contributing docs (#14142)
drop d710f73096 DOC Fix suptitle in LDA_QDA example (#14130)
drop 27bffe63dd CI _changed.html now provides links to compare PR to dev and stable (#14165)
drop a31676b948 EXA Readability of plot_isotonic_regression.py for color blind persons (#14154)
drop 59612a22b3 DOC Fixed Future Warnings by explicitly defining n_estimators = 100 in for the Regressor. (#14159)
drop 9bdcf25fda EXA Fixed Convergence Warnings by changing solver to 'lbfgs' in plot_mlp_alpha.py (#14158)
drop 8b002f2714 MAINT Fix test_fit_csr_matrix failure on master (#14171)
drop 55a7752f2e EXA remove warnings by setting n_quantiles in plot_transformed_target (#14156)
drop f41cd1e856 EXA Use n_quantiles=500 in plot_map_data_to_normal.py (#14149)
drop 0bdd92036d [MRG] MAINT Adds tag categorical to OneHotEncoder (#14068)
drop 62d11120c4 DOC make more obvious that logistic regression is regularized by default (#14093)
drop a717619b8b EXA more color blind friendly colors in plot_map_data_to_normal.py (#wimlds) (#14173)
drop 78ac1ab026 TST Add requires_positive_y estimator tag (#14095)
pick 7f50e82663 FIX Initialize MissingIndicator with error_on_new = False (#13974)
drop be17713d85 MAINT Upgrade CI to PyPy 7.1.1, fix CI failure on master (#13912)
drop eade48eaa2 TST refactor test_truncated_svd (#14140)
drop 24d4b2c2f3 EXA Fixed Convergence Warnings On MLP Training Curves (#14144)
drop a413f88fea TST Fix test_truncated_svd.py::test_explained_variance_compone… (#14178)
drop 11d2539444 MAINT Enable ccache in CircleCI / fix CI on master (#14172)
drop 1dc7b1d84a DOC Add use_line_collection=True to plt.stem to remove warning (#14146)
drop f6923a2971 Fixes #10548 random state description in feature-extraction (#14155)

)

)

jnothman · 2019-06-26T02:23:25Z

What do others think of this as a release? Is early July okay?

Please help identify DOC and maint changes that should be pulled into 0.21.X.

…learn#14187)

rth · 2019-06-26T08:38:01Z

Good idea! Fixing failing tests in #14192 would help with this.

rth · 2019-06-26T08:45:02Z

BTW, do we still intend to release 0.20.4? I keep confusing that tag with 0.21.3 and I might not be the only one. Is there any critical fixes worth backporting to the last version that supports Python 2.7?

jnothman · 2019-06-26T08:55:53Z

We can release 0.20.4 to handle the regressions fixed there: https://github.com/scikit-learn/scikit-learn/milestone/30?closed=1. The StratifiedKFold issue is nasty as a silent bug, but otherwise I'm ambivalent.

ogrisel · 2019-06-29T14:53:13Z

We can release 0.20.4 to handle the regressions fixed there: https://github.com/scikit-learn/scikit-learn/milestone/30?closed=1. The StratifiedKFold issue is nasty as a silent bug, but otherwise I'm ambivalent.

+1 . We could also synchronize joblib that has bugs in the versions shipped in 0.20.3.

…rn#14184)

rth · 2019-07-23T11:57:35Z

I'll try to propose some workaround for #12676 (test_omp_cv fails with MKL and AVX-512) tomorrow.

amueller · 2019-07-23T16:27:18Z

Wait I hadn't seen the StratifiedKFold bug. That means RepeatedStratifiedKFold repeated the same split several times? Or did I misunderstand?

…#14235)

* updated class_weight explanation * glossary_class_weight

…3248)

…arn#14142)

scikit-learn#14154)

…ult (scikit-learn#14093)

…mlp_alpha.py (scikit-learn#14158)

…scikit-learn#14156)

…4149) in order to fix warnings

…4144) * fix convergence warnings * fix convergence warnings * PEP8 * PEP8 * Fix Convergence Warning by changing the Optimization Algorithm * PEP8 * Fixed Future Warnings by explicitly defining n_estimators. * PEP8 * deleted all * Fixed Convergence Warnings * removed changes on unrelated examples * add comment and with statement * PEP8 * context manager fix * fixed indentation * PEP8 * flake8

qinhanmin2014 · 2019-07-29T00:34:42Z

@jnothman I also clean up what's new d49a6f1 74ae6a0
will look at it today

jnothman · 2019-07-29T00:34:51Z

I'll throw in some documentation enhancements for good measure.

jnothman · 2019-07-29T00:57:14Z

Thanks. I didn't notice that change in master but I adopted master's changes in a merge resolution.

qinhanmin2014

need to clean up what's new, otherwise LGTM

jnothman

You're right, I landed up with duplicated change logs

rth

Thanks @jnothman . Will add a few fixes to what's new in #14500 . Opened a separate PR as we want those in master as well, I think?

rth

LGTM, once #14500 is merged and backported here.

This branch currently just includes scikit-learn/scikit-learn/milestone/30?closed=1 and scikit-learn/scikit-learn/milestone/34?closed=1.

So do we want to release 0.20.4 first, and then backport its what new so it would show up on the stable documentation?

jnothman · 2019-07-29T11:50:41Z

Yes, I intended to do that, but it can work in either direction.

jnothman · 2019-07-29T13:32:26Z

Building wheels at https://travis-ci.org/MacPython/scikit-learn-wheels/builds/564978538?utm_source=github_status&utm_medium=notification

Checklist:

update news and what's new date in master and release branch
create tag
update dependencies and release tag at https://github.com/MacPython/scikit-learn-wheels
twine the wheels to PyPI when that's green
https://github.com/scikit-learn/scikit-learn/releases draft
confirm bot detected at https://github.com/conda-forge/scikit-learn-feedstock and wait for merge
https://github.com/scikit-learn/scikit-learn/releases publish
announce on mailing list
(regenerate Dash docs: https://github.com/Kapeli/Dash-User-Contributions/tree/master/docsets/Scikit)

rth · 2019-07-30T08:53:48Z

Glad that it is done. Thanks for making this release happen @jnothman !

jnothman · 2019-07-30T09:33:23Z

No worries. Glad it is done!

jnothman and others added 16 commits June 24, 2019 23:24

TST avoid nose collecting train_test_split as a test (scikit-learn#13951

61a389a

)

FIX plot_tree now displays correct criterion (scikit-learn#13947)

4c62176

MAINT: use explicit value of n_jobs to avoid hangs on Windows (scikit…

a793526

…-learn#13970)

MAINT: test_encoder_dtypes_pandas reads expected dtype from DF (sciki…

e79126d

…t-learn#13997)

MNT DOC fix some sphinx warnings on what's new files (scikit-learn#14049

5f9bee6

)

FIX wrong usage and occurrence of string tag (scikit-learn#14043)

7e874b4

BUG Fix zero division error in GBDTs (scikit-learn#14024)

e07b395

[MRG] fix refit=False error in LogisticRegressionCV (scikit-learn#14087)

f4a0aed

DOC Make parameter, etc listings use small screen width better (sciki…

1f4f011

…t-learn#9503)

BUG Fixes export_text with single feature (scikit-learn#14053)

7c8bf2c

[MRG] Fix NCA parameter type check (scikit-learn#14092)

e673f37

DOC add missing what's new to pr 14092 (scikit-learn#14133)

b5835f6

FIX Initialize MissingIndicator with error_on_new = False (scikit-lea…

d10d1c2

…rn#13974)

MNT bump version to 0.21.3

9f0e674

FIX hist gradient boosting change relied on refactoring

9b82c9f

TST remove test for functionality not included here

425f6be

jnothman force-pushed the for0.21.3 branch from 7035752 to 425f6be Compare June 26, 2019 02:01

jnothman and others added 2 commits June 26, 2019 12:25

DOC move what's new for scikit-learn#13497

dee2745

FIX add abolute tolerance in test_estimate_bandwidth_1sample (scikit-…

0008377

…learn#14187)

rth mentioned this pull request Jun 26, 2019

FIX Test failures in MacPython nightly builds #14192

Closed

[MRG] TST Increases tolerance to match float32 resolution (scikit-lea…

55bb9ec

…rn#14184)

jnothman mentioned this pull request Jul 23, 2019

[MRG] Release 0.20.4 #14443

Merged

11 tasks

DOC Make explicit that groups required *Group* splitter (scikit-learn…

d56d93c

…#14235)

arnaudstiegler and others added 11 commits July 29, 2019 10:31

DOC updated class_weight explanation in glossary (scikit-learn#14121)

51f4047

* updated class_weight explanation * glossary_class_weight

DOC add clarification on random forest default params (scikit-learn#1…

7323081

…3248)

DOC Contributing guide update (scikit-learn#13961)

3d7123e

DOC fixing the missing fetch upstream in contributing docs (scikit-le…

28c0fc2

…arn#14142)

DOC Fix suptitle in LDA_QDA example (scikit-learn#14130)

e6340b5

EXA Readability of plot_isotonic_regression.py for color blind persons (

a3344f9

scikit-learn#14154)

DOC make more obvious that logistic regression is regularized by defa…

fded644

…ult (scikit-learn#14093)

EXA Fixed Convergence Warnings by changing solver to 'lbfgs' in plot_…

a95c1b2

…mlp_alpha.py (scikit-learn#14158)

EXA remove warnings by setting n_quantiles in plot_transformed_target (…

e0cd849

…scikit-learn#14156)

EXA Use n_quantiles=500 in plot_map_data_to_normal.py (scikit-learn#1…

d8b7d46

…4149) in order to fix warnings

qinhanmin2014 approved these changes Jul 29, 2019

View reviewed changes

DOC Clean up what's new by checking out master version

926eda8

jnothman commented Jul 29, 2019

View reviewed changes

rth mentioned this pull request Jul 29, 2019

DOC A few what's new fixes for 0.21.3 #14500

Merged

1 task

rth reviewed Jul 29, 2019

View reviewed changes

DOC A few what's new fixes for 0.21.3 (scikit-learn#14500)

aba85e8

rth approved these changes Jul 29, 2019

View reviewed changes

jnothman added 3 commits July 29, 2019 23:17

DOC adopt what's new for 0.20.4 release

b4faa46

DOC update news for patch releases; set date for 0.21.3 release

fbba9ff

DOC Correct changelog links

08eaecc

jnothman merged commit 08eaecc into scikit-learn:0.21.X Jul 29, 2019

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[MRG] Release 0.21.3 #14188

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