MAINT Remove loguniform fix, use scipy.stats instead, bump scipy version and Ubuntu version in CI #24665

betatim · 2022-10-14T15:18:10Z

Reference Issues/PRs

Continues #23730 and closes #23699 closes

What does this implement/fix? Explain your changes.

This removes sklearn.fixes.loguniform and uses scipy.stats.loguniform instead. It also updates the docs where they refer to loguniform being special because it is provided by sklearn.fixes.

Any other comments?

For now bumping scipy to v1.5.0 to see what the CI says. Will read the discussions on which version exactly to bump to.

PR is on hold because of #24401 (comment). So maybe this PR can be useful at a later point.

ogrisel · 2022-10-14T15:46:27Z

As discussed in #24401 (comment) we want to keep scipy 1.3 / ubuntu 20.04 compat in scikit-learn 1.2 so this PR can only be merged to main after 1.2.X is branched off.

Edit: I just read the last line of the description after commenting...

ogrisel · 2023-02-06T17:01:56Z

@betatim maybe now is the time to revive this :)

betatim · 2023-02-07T13:22:35Z

Let's see what the bots have to say.

ogrisel

I think the minimum version for the dependencies documented in the README.rst file have to be updated manually.

Also there is a paragraph in install.rst that needs to be updated (or removed if no longer applicable):

.. note::

   For installing on PyPy, PyPy3-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+
   are required.

ogrisel

LGTM, assuming the above comments are addressed and the CI is green (on a commit with a message that enabled both a full doc build and a pypy build).

lorentzenchr

LGTM. Once Olivier‘s comments are addressed.

betatim · 2023-02-14T14:36:25Z

The scipy version also appears in the build-system section of pyproject.toml. I guess it makes sense to also update that right?

lorentzenchr · 2023-02-14T14:51:58Z

Could we reduce the occurrences? Updating the min versions should be easy.

…ve-loguniform-fix

betatim · 2023-02-14T16:16:27Z

Could we reduce the occurrences?

I don't think we can template README.md or pyproject.toml

thomasjpfan · 2023-02-14T16:19:00Z

Could we reduce the occurrences? Updating the min versions should be easy.

The source of truth for minimal versions is in https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/_min_dependencies.py. We do have the repeat the versions in other places, like in the README.rst or pyproject.toml, so we do have tests to make sure they are consistent. (For this PR, the consistency check fails, which is expected.)

That being said, we should have a test that checks that pyproject.toml is consistent with _min_dependencies. I opened #25610 to add this test.

thomasjpfan · 2023-02-14T17:04:43Z

From the failing ubuntu-atlas job, they ship SciPy 1.3.3. If we still want to test using Ubuntu's SciPy, we would need to update to 22.04LTS: https://packages.ubuntu.com/jammy/python3-scipy

thomasjpfan · 2023-02-14T17:16:18Z

As for the note in install.rst about PyPy, I would remove it. SciPy does not provide PyPy wheels on PyPi, so it is hard to install with pip. Ultimately, the simplest way to use PyPy + scikit-learn is with conda-forge:

mamba create -n pypy pypy scikit-learn

For newer versions of PyPy, there are still issues with scikit-learn PyPy migration: conda-forge/scikit-learn-feedstock#213

betatim · 2023-02-15T07:31:08Z

What does the "atlas" refer to in the Ubuntu job? The job runs on Ubuntu 20.04 which is a LTS version, with support ending in 2025. So I think installing scikit-learn on 20.04 should be something we test (and support). But maybe "atlas" refers to some particular variant or something?

This would suggest that we can't increase the minimum scipy version to 1.5.0 until April 2025.

I've removed the PyPy specific note in install.rst.

lorentzenchr · 2023-02-15T19:51:15Z

Can we merge? (after sync with main)

thomasjpfan · 2023-02-15T21:33:25Z

What does the "atlas" refer to in the Ubuntu job?

Atlas refers to the Linear Algebra library shipped with Ubuntu: https://packages.ubuntu.com/focal/libatlas3-base

betatim · 2023-02-17T07:58:55Z

Can we merge? (after sync with main)

We need to decide if supporting ATLAS (on Ubuntu 20.04) is something scikit-learn cares about. If we bump scipy to 1.5.0 we lose this. If we don't care about 20.04 + ATLAS then we can either remove the CI job that tests for it or increase the version of Ubuntu the job uses.

betatim · 2023-02-17T08:01:52Z

(aside: why the sync with main? My intuition is that it is only needed when there is a conflict, and otherwise we don't need it? As in, I don't quite understand why GitHub even shows the button :-/)

lorentzenchr · 2023-02-23T18:15:50Z

The last two issues for increasing scipy where #19705 and #21460.

Ubuntu 18.04 LTS will end standard support in April 2023. As our 1.3 release will be later (May or June), I guess it's sound to go for Ubuntu 20.04 LTS. If that is still with Atlas (BLAS), then fine.

Maybe we should open a separate issue for that, as this PR is for loguniform😄

lorentzenchr · 2023-02-23T18:17:04Z

aside: why the sync with main

Good point. I didn't notice that this github status is noise/nonsense.

jjerphan · 2023-03-23T08:59:38Z

Hi all, I think we already test against Ubuntu 20.04 with ATLAS:

scikit-learn/azure-pipelines.yml

Lines 167 to 221 in 18af550

    
           - template: build_tools/azure/posix.yml 
        
             parameters: 
        
               name: Linux 
        
               vmImage: ubuntu-20.04 
        
               dependsOn: [linting, git_commit, Ubuntu_Jammy_Jellyfish] 
        
               # Runs when dependencies succeeded or skipped 
        
               condition: | 
        
                 and( 
        
                   not(or(failed(), canceled())), 
        
                   not(contains(dependencies['git_commit']['outputs']['commit.message'], '[ci skip]')) 
        
                 ) 
        
               matrix: 
        
                 # Linux environment to test that scikit-learn can be built against 
        
                 # versions of numpy, scipy with ATLAS that comes with Ubuntu Focal 20.04 
        
                 # i.e. numpy 1.17.4 and scipy 1.3.3 
        
                 ubuntu_atlas: 
        
                   DISTRIB: 'ubuntu' 
        
                   LOCK_FILE: './build_tools/azure/ubuntu_atlas_lock.txt' 
        
                   COVERAGE: 'false' 
        
                   SKLEARN_TESTS_GLOBAL_RANDOM_SEED: '1'  # non-default seed 
        
                 # Linux + Python 3.8 build with OpenBLAS 
        
                 py38_conda_defaults_openblas: 
        
                   DISTRIB: 'conda' 
        
                   LOCK_FILE: './build_tools/azure/py38_conda_defaults_openblas_linux-64_conda.lock' 
        
                   SKLEARN_ENABLE_DEBUG_CYTHON_DIRECTIVES: '1' 
        
                   SKLEARN_RUN_FLOAT32_TESTS: '1' 
        
                   SKLEARN_TESTS_GLOBAL_RANDOM_SEED: '2'  # non-default seed 
        
                 # Linux environment to test the latest available dependencies. 
        
                 # It runs tests requiring lightgbm, pandas and PyAMG. 
        
                 pylatest_pip_openblas_pandas: 
        
                   DISTRIB: 'conda-pip-latest' 
        
                   LOCK_FILE: './build_tools/azure/pylatest_pip_openblas_pandas_linux-64_conda.lock' 
        
                   CHECK_PYTEST_SOFT_DEPENDENCY: 'true' 
        
                   CHECK_WARNINGS: 'true' 
        
                   SKLEARN_TESTS_GLOBAL_RANDOM_SEED: '3'  # non-default seed 
        
           - template: build_tools/azure/posix-docker.yml 
        
             parameters: 
        
               name: Linux_Docker 
        
               vmImage: ubuntu-20.04 
        
               dependsOn: [linting, git_commit, Ubuntu_Jammy_Jellyfish] 
        
               # Runs when dependencies succeeded or skipped 
        
               condition: | 
        
                 and( 
        
                   not(or(failed(), canceled())), 
        
                   not(contains(dependencies['git_commit']['outputs']['commit.message'], '[ci skip]')) 
        
                 ) 
        
               matrix: 
        
                 debian_atlas_32bit: 
        
                   DOCKER_CONTAINER: 'i386/debian:11.2' 
        
                   DISTRIB: 'debian-32' 
        
                   LOCK_FILE: './build_tools/azure/debian_atlas_32bit_lock.txt' 
        
                   # disable pytest xdist due to unknown bug with 32-bit container 
        
                   PYTEST_XDIST_VERSION: 'none' 
        
                   SKLEARN_TESTS_GLOBAL_RANDOM_SEED: '4'  # non-default seed

Hence is resolving the conda lock-files merge conflicts sufficient for this PR to be merged?

betatim · 2023-03-23T09:08:06Z

We test Ubuntu 20.04 with ATLAS in the scikit-learn.scikit-learn (Linux ubuntu_atlas) job, and this is the one that failed. This is why I think we need to decide if supporting 20.04 + ATLAS is something we care about or not.

ogrisel · 2023-03-23T09:24:00Z

We care about making sure that scikit-learn can work with any commonly shipped implementation of BLAS. But we could consider bumping the dependencies to Ubuntu 22.04 LTS for 1.3 as @thomasjpfan suggested in #24665 (comment).

The fact that this build uses ATLAS or any other BLAS implementation is irrelevant for the loguniform fix itself (I think).

ogrisel · 2023-03-23T09:27:58Z

Could someone re-trigger this PR once with ubuntu 20.04 LTS to see the original error log (it has expired) to confirm the above. And if so, let's try to bump up the Azure build to 22.04 LTS to see if would resolve that last failure as expected.

betatim · 2023-03-23T09:30:57Z

I don't know how to bump the build :( But I can tell you that the problem isn't with loguniform, it is just a question of which scipy version you install (like you said).

ogrisel · 2023-03-23T09:44:28Z

Let's try to bump directly the CI config to 22.04 LTS. You might also need to adapt the matching entry in build_tools/update_environments_and_lock_files.py and re-run it.

With Ubuntu 20.04 we can not get a new enough version of scipy, and 22.04 is the latest LTS release.

lorentzenchr · 2023-03-23T12:35:02Z

azure-pipelines.yml

+- template: build_tools/azure/posix.yml
+  parameters:
+    name: Linux
+    vmImage: ubuntu-20.04


Suggested change

vmImage: ubuntu-20.04

vmImage: ubuntu-22.04

? I‘m confused.

I wasn't sure if we want to upgrade all Ubuntu based tests or just the one using ATLAS. In the end I went with "just the ATLAS one" because for the other ones we can still run on 20.04. I think it is nice to keep old versions and test against them for as long as possible/only upgrade when you have to.

lorentzenchr

Is is now mergable if CI is green?

ogrisel

LGTM again.

jjerphan

LGTM even if I think having the CI setup be updated in another PR would have been clearer.

I have updated the title to include a MAINT prefix. Should we mention something about the CI in the title?

Co-authored-by: Olivier Grisel <[email protected]>

* MAINT Clean deprecated losses in (hist) gradient boosting for 1.3 (scikit-learn#25834) * MAINT Clean deprecation of normalize in calibration_curve for 1.3 (scikit-learn#25833) * BLD Clean command removes generated from cython templates (scikit-learn#25839) * PERF Implement `PairwiseDistancesReduction` backend for `KNeighbors.predict_proba` (scikit-learn#24076) Signed-off-by: Julien Jerphanion <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> * MAINT Added Parameter Validation for datasets.make_circles (scikit-learn#25848) Co-authored-by: jeremiedbb <[email protected]> * MNT use a single job by default with sphinx build (scikit-learn#25836) * BLD Generate warning automatically for templated cython files (scikit-learn#25842) * MAINT parameter validation for sklearn.datasets.fetch_lfw_people (scikit-learn#25820) Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameters validation for metrics.fbeta_score (scikit-learn#25841) * TST add global_random_seed fixture to sklearn/covariance/tests/test_robust_covariance.py (scikit-learn#25821) * MAINT Parameter validation for linear_model.orthogonal_mp (scikit-learn#25817) * TST activate common tests for TSNE (scikit-learn#25374) * CI Update lock files (scikit-learn#25849) * MAINT Added Parameter Validation for metrics.mean_gamma_deviance (scikit-learn#25853) * MAINT Parameters validation for feature_selection.mutual_info_regression (scikit-learn#25850) * MAINT parameter validation metrics.class_likelihood_ratios (scikit-learn#25863) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Ensure disjoint interval constraints (scikit-learn#25797) * MAINT Parameters validation for utils.gen_batches (scikit-learn#25864) * TST use global_random_seed in test_dict_vectorizer.py (scikit-learn#24533) * TST use global_random_seed in test_pls.py (scikit-learn#24526) Co-authored-by: jeremiedbb <[email protected]> * TST use global_random_seed in test_gpc.py (scikit-learn#24600) Co-authored-by: jeremiedbb <[email protected]> * DOC Fix overlapping plot axis in bench_sample_without_replacement.py (scikit-learn#25870) * MAINT Use contiguous memoryviews in _random.pyx (scikit-learn#25871) * MAINT parameter validation sklearn.datasets.fetch_lfw_pair (scikit-learn#25857) * MAINT Parameters validation for metrics.classification_report (scikit-learn#25868) * Empty commit * DOC fix docstring dtype parameter in OrdinalEncoder (scikit-learn#25877) * MAINT Clean up depreacted "log" loss of SGDClassifier for 1.3 (scikit-learn#25865) * ENH Adds TargetEncoder (scikit-learn#25334) Co-authored-by: Andreas Mueller <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Jovan Stojanovic <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> * CI make it possible to cancel running Azure jobs (scikit-learn#25876) * MAINT Clean-up deprecated if_delegate_has_method for 1.3 (scikit-learn#25879) * MAINT Parameter validation for tree.export_text (scikit-learn#25867) * DOC impact of `tol` for solvers in RidgeClassifier (scikit-learn#25530) * MAINT Parameters validation for metrics.hinge_loss (scikit-learn#25880) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for metrics.ndcg_score (scikit-learn#25885) * ENH KMeans initialization account for sample weights (scikit-learn#25752) Co-authored-by: jeremiedbb <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]> * TST use global_random_seed in sklearn/tests/test_dummy.py (scikit-learn#25884) * DOC improve calibration user guide (scikit-learn#25687) * ENH Support for sparse matrices added to `sklearn.metrics.silhouette_samples` (scikit-learn#24677) Co-authored-by: Sahil Gupta <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> * MAINT validate_params for plot_tree (scikit-learn#25882) Co-authored-by: Itay <[email protected]> * MAINT add missing space in error message in SVM (scikit-learn#25913) * FIX Adds requires_y tag to TargetEncoder (scikit-learn#25917) * MAINT Consistent cython types continued (scikit-learn#25810) * TST Speed-up common tests of DictionaryLearning (scikit-learn#25892) * TST Speed-up test_dbscan_optics_parity (scikit-learn#25893) * ENH add np.nan option for zero_division in precision/recall/f-score (scikit-learn#25531) Co-authored-by: Guillaume Lemaitre <[email protected]> * MAINT Parameters validation for datasets.make_low_rank_matrix (scikit-learn#25901) * MAINT Parameter validation for metrics.cluster.adjusted_mutual_info_score (scikit-learn#25898) Co-authored-by: Jérémie du Boisberranger <[email protected]> * TST Speed-up test_partial_dependence.test_output_shape (scikit-learn#25895) Co-authored-by: Thomas J. Fan <[email protected]> * MAINT Parameters validation for datasets.make_regression (scikit-learn#25899) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for metrics.mean_squared_log_error (scikit-learn#25924) * TST Use global_random_seed in tests/test_naive_bayes.py (scikit-learn#25890) * TST add global_random_seed fixture to sklearn/datasets/tests/test_covtype.py (scikit-learn#25904) Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameters validation for datasets.make_multilabel_classification (scikit-learn#25920) * Fixed feature mapping typo (scikit-learn#25934) * MAINT switch to newer codecov uploader (scikit-learn#25919) Co-authored-by: Loïc Estève <[email protected]> * TST Speed-up test suite when using pytest-xdist (scikit-learn#25918) * DOC update license year to 2023 (scikit-learn#25936) * FIX Remove spurious feature names warning in IsolationForest (scikit-learn#25931) * TST fix unstable test_newrand_set_seed (scikit-learn#25940) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Clean-up deprecated max_features="auto" in trees/forests/gb (scikit-learn#25941) * MAINT LogisticRegression informative error msg when penaly=elasticnet and l1_ratio is None (scikit-learn#25925) Co-authored-by: jeremiedbb <[email protected]> * MAINT Clean-up remaining SGDClassifier(loss="log") (scikit-learn#25938) * FIX Fixes pandas extension arrays in check_array (scikit-learn#25813) * FIX Fixes pandas extension arrays with objects in check_array (scikit-learn#25814) * CI Disable pytest-xdist in pylatest_pip_openblas_pandas build (scikit-learn#25943) * MAINT remove deprecated call to resources.content (scikit-learn#25951) * DOC note on calibration impact on ranking (scikit-learn#25900) * Remove loguniform fix, use scipy.stats instead (scikit-learn#24665) Co-authored-by: Olivier Grisel <[email protected]> * MAINT Fix broken links in cluster.dbscan module (scikit-learn#25958) * DOC Fix lars Xy shape (scikit-learn#25952) * ENH Add drop_intermediate parameter to metrics.precision_recall_curve (scikit-learn#24668) Co-authored-by: Guillaume Lemaitre <[email protected]> * FIX improve error message when computing NDCG with a single document (scikit-learn#25672) Co-authored-by: Guillaume Lemaitre <[email protected]> * MAINT introduce _get_response_values and _check_response_methods (scikit-learn#23073) Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Extend message for large sparse matrices support (scikit-learn#25961) Co-authored-by: Meekail Zain <[email protected]> * MAINT Parameters validation for datasets.make_gaussian_quantiles (scikit-learn#25959) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.d2_tweedie_score (scikit-learn#25975) * MAINT Parameters validation for datasets.make_hastie_10_2 (scikit-learn#25967) * MAINT Parameters validation for preprocessing.minmax_scale (scikit-learn#25962) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for datasets.make_checkerboard (scikit-learn#25955) * MAINT Parameters validation for datasets.make_biclusters (scikit-learn#25945) * MAINT Parameters validation for datasets.make_moons (scikit-learn#25971) * DOC replace deviance by loss in docstring of GradientBoosting (scikit-learn#25968) * MAINT Fix broken link in feature_selection/_univariate_selection.py (scikit-learn#25984) * DOC Update model_persistence.rst to fix skops example (scikit-learn#25993) Co-authored-by: adrinjalali <[email protected]> * DOC Specified meaning for max_patches=None in extract_patches_2d (scikit-learn#25996) * DOC document that last step is never cached in pipeline (scikit-learn#25995) Co-authored-by: Guillaume Lemaitre <[email protected]> * FIX SequentialFeatureSelector throws IndexError when cv is a generator (scikit-learn#25973) * ENH Adds infrequent categories support to OrdinalEncoder (scikit-learn#25677) Co-authored-by: Tim Head <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Andreas Mueller <[email protected]> * MAINT make plot_digits_denoising deterministic by fixing random state (scikit-learn#26004) * DOC improve example of PatchExtractor (scikit-learn#26002) * MAINT Parameters validation for datasets.make_friedman2 (scikit-learn#25986) * MAINT Parameters validation for datasets.make_friedman3 (scikit-learn#25989) * MAINT Parameters validation for datasets.make_sparse_uncorrelated (scikit-learn#26001) * MAINT Parameters validation for datasets.make_spd_matrix (scikit-learn#26003) * MAINT Parameters validation for datasets.make_sparse_spd_matrix (scikit-learn#26009) * DOC Added the meanings of default=None for PatchExtractor parameters (scikit-learn#26005) * MAINT remove unecessary check covered by parameter validation framework (scikit-learn#26014) * MAINT Consistent cython types from _typedefs (scikit-learn#25942) Co-authored-by: Julien Jerphanion <[email protected]> * MAINT Parameters validation for datasets.make_swiss_roll (scikit-learn#26020) * MAINT Parameters validation for datasets.make_s_curve (scikit-learn#26022) * MAINT Parameters validation for datasets.make_blobs (scikit-learn#25983) Co-authored-by: Guillaume Lemaitre <[email protected]> * DOC fix SplineTransformer include_bias docstring (scikit-learn#26018) * ENH RocCurveDisplay add option to plot chance level (scikit-learn#25987) * DOC show from_estimator and from_predictions for Displays (scikit-learn#25994) * EXA Fix rst in plot_partial_dependence (scikit-learn#26028) * CI Adds coverage to docker jobs on Azure (scikit-learn#26027) Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> * API Replace `n_iter` in `Bayesian Ridge` and `ARDRegression` (scikit-learn#25697) Co-authored-by: Guillaume Lemaitre <[email protected]> * CLN Make _NumPyAPIWrapper naming consistent to _ArrayAPIWrapper (scikit-learn#26039) * CI disable coverage on Windows to keep CI times reasonable (scikit-learn#26052) * DOC Use Scientific Python Plausible instance for analytics (scikit-learn#25547) * MAINT Parameters validation for sklearn.preprocessing.scale (scikit-learn#26036) * MAINT Parameters validation for sklearn.metrics.pairwise.haversine_distances (scikit-learn#26047) * MAINT Parameters validation for sklearn.metrics.pairwise.laplacian_kernel (scikit-learn#26048) * MAINT Parameters validation for sklearn.metrics.pairwise.linear_kernel (scikit-learn#26049) * MAINT Parameters validation for sklearn.metrics.silhouette_samples (scikit-learn#26053) * MAINT Parameters validation for sklearn.preprocessing.add_dummy_feature (scikit-learn#26058) * Added Parameter Validation for metrics.cluster.normalized_mutual_info_score() (scikit-learn#26060) * DOC Typos in HistGradientBoosting documentation (scikit-learn#26057) * TST add global_random_seed fixture to sklearn/datasets/tests/test_rcv1.py (scikit-learn#26043) * MAINT Parameters validation for sklearn.metrics.pairwise.cosine_similarity (scikit-learn#26006) Co-authored-by: Jérémie du Boisberranger <[email protected]> * ENH Adds isdtype to Array API wrapper (scikit-learn#26029) * MAINT Parameters validation for sklearn.metrics.silhouette_score (scikit-learn#26054) Co-authored-by: Jérémie du Boisberranger <[email protected]> * FIX fix spelling mistake in _NumPyAPIWrapper (scikit-learn#26064) * CI ignore more non-library Python files in codecov (scikit-learn#26059) * MAINT Parameters validation for sklearn.metrics.pairwise.cosine_distances (scikit-learn#26046) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Introduce BinaryClassifierCurveDisplayMixin (scikit-learn#25969) Co-authored-by: Jérémie du Boisberranger <[email protected]> * ENH Forces shape to be tuple when using Array API's reshape (scikit-learn#26030) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Tim Head <[email protected]> * MAINT Parameters validation for sklearn.metrics.pairwise.paired_euclidean_distances (scikit-learn#26073) * MAINT Parameters validation for sklearn.metrics.pairwise.paired_manhattan_distances (scikit-learn#26074) * MAINT Parameters validation for sklearn.metrics.pairwise.paired_cosine_distances (scikit-learn#26075) * MAINT Parameters validation for sklearn.preprocessing.binarize (scikit-learn#26076) * MAINT Parameters validation for metrics.explained_variance_score (scikit-learn#26079) * DOC use correct template name for displays (scikit-learn#26081) * MAINT Parameters validation for sklearn.preprocessing.maxabs_scale (scikit-learn#26077) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.preprocessing.label_binarize (scikit-learn#26078) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT parameter validation for d2_absolute_error_score (scikit-learn#26066) Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameter validation for roc_auc_score (scikit-learn#26007) Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameters validation for sklearn.preprocessing.normalize (scikit-learn#26069) Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameter validation for metrics.cluster.fowlkes_mallows_score (scikit-learn#26080) Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameters validation for compose.make_column_transformer (scikit-learn#25897) Co-authored-by: jeremiedbb <[email protected]> * MAINT Parameters validation for sklearn.metrics.pairwise.polynomial_kernel (scikit-learn#26070) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.pairwise.rbf_kernel (scikit-learn#26071) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.pairwise.sigmoid_kernel (scikit-learn#26072) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Param validation: constraint for numeric missing values (scikit-learn#26085) * FIX Adds support for negative values in categorical features in gradient boosting (scikit-learn#25629) Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Tim Head <[email protected]> * MAINT Fix C warning in Cython module splitting.pyx (scikit-learn#26051) * MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` (scikit-learn#26068) * FIX Fixes memory regression for inspecting extension arrays (scikit-learn#26106) * PERF set openmp to use only physical cores by default (scikit-learn#26082) * MNT Update black to 23.3.0 (scikit-learn#26110) * MNT Adds black commit to git-blame-ignore-revs (scikit-learn#26111) * MAINT Parameters validation for sklearn.metrics.pair_confusion_matrix (scikit-learn#26107) * MAINT Parameters validation for sklearn.metrics.mean_poisson_deviance (scikit-learn#26104) * DOC Use notebook style in plot_lof_outlier_detection.py (scikit-learn#26017) Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> * MAINT utils._fast_dict uses types from utils._typedefs (scikit-learn#26025) * DOC remove sparse-matrix for `y` in ElasticNet (scikit-learn#26127) * ENH add exponential loss (scikit-learn#25965) * MAINT Parameters validation for sklearn.preprocessing.robust_scale (scikit-learn#26086) * MAINT Parameters validation for sklearn.datasets.fetch_rcv1 (scikit-learn#26126) * MAINT Parameters validation for sklearn.metrics.adjusted_rand_score (scikit-learn#26134) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.calinski_harabasz_score (scikit-learn#26135) * MAINT Parameters validation for sklearn.metrics.davies_bouldin_score (scikit-learn#26136) * MAINT: remove `from numpy.math cimport` statements (scikit-learn#26143) * MAINT Parameters validation for sklearn.inspection.permutation_importance (scikit-learn#26145) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.cluster.homogeneity_completeness_v_measure (scikit-learn#26137) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.rand_score (scikit-learn#26138) Co-authored-by: Jérémie du Boisberranger <[email protected]> * DOC update comment in metrics/tests/test_classification.py (scikit-learn#26150) * CI small cleanup of Cirrus CI test script (scikit-learn#26168) * MAINT remove deprecated is_categorical_dtype (scikit-learn#26156) * DOC Add skforecast to related projects page (scikit-learn#26133) Co-authored-by: Thomas J. Fan <[email protected]> * FIX Keeps namedtuple's class when transform returns a tuple (scikit-learn#26121) * DOC corrected letter case for better readability in sklearn/metrics/_classification.py / (scikit-learn#26169) * MAINT Parameters validation for sklearn.preprocessing.power_transform (scikit-learn#26142) * FIX `roc_auc_score` now uses `y_prob` instead of `y_pred` (scikit-learn#26155) * MAINT Parameters validation for sklearn.datasets.load_iris (scikit-learn#26177) * MAINT Parameters validation for sklearn.datasets.load_diabetes (scikit-learn#26166) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.datasets.load_breast_cancer (scikit-learn#26165) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.metrics.cluster.entropy (scikit-learn#26162) * MAINT Parameters validation for sklearn.datasets.fetch_species_distributions (scikit-learn#26161) Co-authored-by: Jérémie du Boisberranger <[email protected]> * ASV Fix tol in SGDRegressorBenchmark (scikit-learn#26146) Co-authored-by: jeremie du boisberranger <[email protected]> * MNT use api.openml.org URLs for fetch_openml (scikit-learn#26171) * MAINT Parameters validation for sklearn.utils.resample (scikit-learn#26139) * MAINT make it explicit that additive_chi2_kernel does not accept sparse matrix (scikit-learn#26178) * MNT fix circleci link in README.rst (scikit-learn#26183) * CI Fix circleci artifact redirector action (scikit-learn#26181) * GOV introduce rights for groups as discussed in SLEP019 (scikit-learn#25753) Co-authored-by: Julien <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> * MAINT Parameters validation for sklearn.neighbors.sort_graph_by_row_values (scikit-learn#26173) Co-authored-by: Jérémie du Boisberranger <[email protected]> * FIX improve convergence criterion for LogisticRegression(penalty="l1", solver='liblinear') (scikit-learn#25214) Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> * MAINT Fix several typos in src and doc files (scikit-learn#26187) * PERF fix overhead of _rescale_data in LinearRegression (scikit-learn#26207) * ENH add Huber loss (scikit-learn#25966) * MAINT Refactor GraphicalLasso and graphical_lasso (scikit-learn#26033) Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Cython linting (scikit-learn#25861) * DOC Add JupyterLite button in example gallery (scikit-learn#25887) * MAINT Parameters validation for sklearn.covariance.ledoit_wolf_shrinkage (scikit-learn#26200) * MAINT Parameters validation for sklearn.datasets.load_linnerud (scikit-learn#26199) * MAINT Parameters validation for sklearn.datasets.load_wine (scikit-learn#26196) * DOC Added redirect to Provost paper + minor refactor (scikit-learn#26223) * MAINT Parameter Validation for `covariance.graphical_lasso` (scikit-learn#25053) Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.datasets.load_digits (scikit-learn#26195) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.preprocessing.quantile_transform (scikit-learn#26144) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.model_selection.cross_validate (scikit-learn#26129) Co-authored-by: jeremiedbb <[email protected]> * DOC Adds TargetEncoder example explaining the internal CV (scikit-learn#26185) Co-authored-by: Tim Head <[email protected]> * spelling mistake corrected in documentation for script `plot_document_clustering.py` (scikit-learn#26228) Co-authored-by: Olivier Grisel <[email protected]> * FIX possible UnboundLocalError in fetch_openml (scikit-learn#26236) * ENH Adds PyTorch support to LinearDiscriminantAnalysis (scikit-learn#25956) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Tim Head <[email protected]> * MNT Use fixed version of Pyodide (scikit-learn#26247) * MNT Reset transform_output default in example to fix doc build build (scikit-learn#26269) * DOC Update example plot_nearest_centroid.py (scikit-learn#26263) * MNT reduce JupyterLite build size (scikit-learn#26246) * DOC term -> meth in GradientBoosting (scikit-learn#26225) * MNT speed-up html-noplot build (scikit-learn#26245) Co-authored-by: Thomas J. Fan <[email protected]> * MNT Use copy=False when creating DataFrames (scikit-learn#26272) * MAINT Parameters validation for sklearn.model_selection.permutation_test_score (scikit-learn#26230) * MAINT Parameters validation for sklearn.datasets.clear_data_home (scikit-learn#26259) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.datasets.load_files (scikit-learn#26203) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.datasets.get_data_home (scikit-learn#26260) Co-authored-by: Jérémie du Boisberranger <[email protected]> * DOC Fix y-axis plot labels in permutation test score example (scikit-learn#26240) * MAINT cython-lint ignores asv_benchmarks (scikit-learn#26282) * MAINT Parameter validation for metrics.cluster._supervised (scikit-learn#26258) Co-authored-by: Jérémie du Boisberranger <[email protected]> * DOC Improve docstring for tol in SequentialFeatureSelector (scikit-learn#26271) * MAINT Parameters validation for sklearn.datasets.load_sample_image (scikit-learn#26226) Co-authored-by: Jérémie du Boisberranger <[email protected]> * DOC Consistent param type for pos_label (scikit-learn#26237) * DOC Minor grammar fix to imputation docs (scikit-learn#26283) * MAINT Parameters validation for sklearn.calibration.calibration_curve (scikit-learn#26198) Co-authored-by: jeremie du boisberranger <[email protected]> * MAINT Parameters validation for sklearn.inspection.partial_dependence (scikit-learn#26209) Co-authored-by: jeremie du boisberranger <[email protected]> * MAINT Parameters validation for sklearn.model_selection.validation_curve (scikit-learn#26229) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MAINT Parameters validation for sklearn.model_selection.learning_curve (scikit-learn#26227) Co-authored-by: jeremie du boisberranger <[email protected]> * MNT Remove deprecated pandas.api.types.is_sparse (scikit-learn#26287) * CI Use Trusted Publishers for uploading wheels to PyPI (scikit-learn#26249) * MAINT Parameters validation for sklearn.metrics.pairwise.manhattan_distances (scikit-learn#26122) * PERF revert openmp use in csr_row_norms (scikit-learn#26275) * MAINT Parameters validation for metrics.check_scoring (scikit-learn#26041) Co-authored-by: Jérémie du Boisberranger <[email protected]> * MNT Improve error message when checking classification target is of a non-regression type (scikit-learn#26281) Co-authored-by: Adrin Jalali <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> * DOC fix link to User Guide encoder_infrequent_categories (scikit-learn#26309) * MNT remove unused args in _predict_regression_tree_inplace_fast_dense (scikit-learn#26314) * ENH Adds missing value support for trees (scikit-learn#23595) Co-authored-by: Tim Head <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> * CLN Clean up logic in validate_data and cast_to_ndarray (scikit-learn#26300) * MAINT refactor scorer using _get_response_values (scikit-learn#26037) Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: Adrin Jalali <[email protected]> * DOC Add HGBDT to "see also" section of random forests (scikit-learn#26319) Co-authored-by: ArturoAmorQ <[email protected]> Co-authored-by: Tim Head <[email protected]> * MNT Bump Github Action labeler version to use newer Node (scikit-learn#26302) * FIX thresholds should not exceed 1.0 with probabilities in `roc_curve` (scikit-learn#26194) Co-authored-by: Olivier Grisel <[email protected]> * ENH Allow for appropriate dtype us in `preprocessing.PolynomialFeatures` for sparse matrices (scikit-learn#23731) Co-authored-by: Aleksandr Kokhaniukov <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> * DOC Fix minor typo (scikit-learn#26327) * MAINT bump minimum version for pytest (scikit-learn#26184) Co-authored-by: Loïc Estève <[email protected]> Co-authored-by: Adrin Jalali <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> * DOC fix return type in isotonic_regression (scikit-learn#26332) * FIX fix available_if for MultiOutputRegressor.partial_fit (scikit-learn#26333) Co-authored-by: Guillaume Lemaitre <[email protected]> * FIX make pipeline pass check_estimator (scikit-learn#26325) * FEA Add multiclass support to `average_precision_score` (scikit-learn#24769) Co-authored-by: Geoffrey <[email protected]> Co-authored-by: gbolmier <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> --------- Signed-off-by: Julien Jerphanion <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: Meekail Zain <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: zeeshan lone <[email protected]> Co-authored-by: jeremiedbb <[email protected]> Co-authored-by: Adrin Jalali <[email protected]> Co-authored-by: Shiva chauhan <[email protected]> Co-authored-by: AymericBasset <[email protected]> Co-authored-by: Maren Westermann <[email protected]> Co-authored-by: Nishu Choudhary <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Loïc Estève <[email protected]> Co-authored-by: Benedek Harsanyi <[email protected]> Co-authored-by: Pooja Subramaniam <[email protected]> Co-authored-by: Rushil Desai <[email protected]> Co-authored-by: Xiao Yuan <[email protected]> Co-authored-by: Omar Salman <[email protected]> Co-authored-by: 2357juan <[email protected]> Co-authored-by: Théophile Baranger <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Andreas Mueller <[email protected]> Co-authored-by: Jovan Stojanovic <[email protected]> Co-authored-by: Rahil Parikh <[email protected]> Co-authored-by: Bharat Raghunathan <[email protected]> Co-authored-by: Sortofamudkip <[email protected]> Co-authored-by: Gleb Levitski <[email protected]> Co-authored-by: Christian Lorentzen <[email protected]> Co-authored-by: Ashwin Mathur <[email protected]> Co-authored-by: Sahil Gupta <[email protected]> Co-authored-by: Veghit <[email protected]> Co-authored-by: Itay <[email protected]> Co-authored-by: precondition <[email protected]> Co-authored-by: Marc Torrellas Socastro <[email protected]> Co-authored-by: Dominic Fox <[email protected]> Co-authored-by: futurewarning <[email protected]> Co-authored-by: Yao Xiao <[email protected]> Co-authored-by: Joey Ortiz <[email protected]> Co-authored-by: Tim Head <[email protected]> Co-authored-by: Christian Veenhuis <[email protected]> Co-authored-by: adienes <[email protected]> Co-authored-by: Dave Berenbaum <[email protected]> Co-authored-by: Lene Preuss <[email protected]> Co-authored-by: A.H.Mansouri <[email protected]> Co-authored-by: Boris Feld <[email protected]> Co-authored-by: Carla J <[email protected]> Co-authored-by: windiana42 <[email protected]> Co-authored-by: mdarii <[email protected]> Co-authored-by: murezzda <[email protected]> Co-authored-by: Peter Piontek <[email protected]> Co-authored-by: John Pangas <[email protected]> Co-authored-by: Dmitry Nesterov <[email protected]> Co-authored-by: Yuchen Zhou <[email protected]> Co-authored-by: Ekaterina Butyugina <[email protected]> Co-authored-by: Jiawei Zhang <[email protected]> Co-authored-by: Ansam Zedan <[email protected]> Co-authored-by: genvalen <[email protected]> Co-authored-by: farhan khan <[email protected]> Co-authored-by: Arturo Amor <[email protected]> Co-authored-by: Jiawei Zhang <[email protected]> Co-authored-by: Ralf Gommers <[email protected]> Co-authored-by: Jessicakk0711 <[email protected]> Co-authored-by: Ankur Singh <[email protected]> Co-authored-by: Seoeun(Sun☀️) Hong <[email protected]> Co-authored-by: Nightwalkx <[email protected]> Co-authored-by: VIGNESH D <[email protected]> Co-authored-by: Vincent-violet <[email protected]> Co-authored-by: Elabonga Atuo <[email protected]> Co-authored-by: Tom Dupré la Tour <[email protected]> Co-authored-by: André Pedersen <[email protected]> Co-authored-by: Ashish Dutt <[email protected]> Co-authored-by: Phil <[email protected]> Co-authored-by: Stanislav (Stanley) Modrak <[email protected]> Co-authored-by: hujiahong726 <[email protected]> Co-authored-by: James Dean <[email protected]> Co-authored-by: ArturoAmorQ <[email protected]> Co-authored-by: Aleksandr Kokhaniukov <[email protected]> Co-authored-by: c-git <[email protected]> Co-authored-by: annegnx <[email protected]> Co-authored-by: Geoffrey <[email protected]> Co-authored-by: gbolmier <[email protected]>

betatim added 2 commits October 14, 2022 17:01

Remove loguniform fix, use scipy.stats instead

acda7e4

Bump scipy to v1.5.0

15ac96a

github-actions bot added the module:utils label Oct 14, 2022

jeremiedbb added this to the 1.3 milestone Oct 14, 2022

betatim marked this pull request as ready for review November 8, 2022 09:17

betatim added 3 commits February 7, 2023 11:16

Merge branch 'main' into remove-loguniform-fix

d16c759

Remvove obsolete loguniform fix

a2e28c3

Updated environment and lock files for scipy 1.5

ab355e6

ogrisel mentioned this pull request Feb 14, 2023

FEA add newton-lsmr solver to LogisticRegression and GLMs #25462

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ogrisel added the No Changelog Needed label Feb 14, 2023

Merge branch 'main' into remove-loguniform-fix

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betatim added 2 commits February 14, 2023 17:14

Update scipy version in README and pyproject.toml

98162bc

Merge remote-tracking branch 'origin/remove-loguniform-fix' into remo…

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…ve-loguniform-fix

thomasjpfan mentioned this pull request Feb 14, 2023

MAINT Check pyproject toml is consistent with min_dependencies #25610

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Remove PyPy specific install note

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betatim added 2 commits March 23, 2023 10:54

Merge branch 'main' into remove-loguniform-fix

202acbd

Update Ubuntua ATLAS CI to use 22.04

8ac6611

With Ubuntu 20.04 we can not get a new enough version of scipy, and 22.04 is the latest LTS release.

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betatim force-pushed the remove-loguniform-fix branch from bb6619c to 153aee9 Compare March 23, 2023 14:40

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ogrisel enabled auto-merge (squash) March 23, 2023 15:35

jjerphan changed the title ~~Remove loguniform fix, use scipy.stats instead~~ MAINT Remove loguniform fix, use scipy.stats instead Mar 23, 2023

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ogrisel merged commit 49a937e into scikit-learn:main Mar 23, 2023

betatim deleted the remove-loguniform-fix branch March 23, 2023 18:08

betatim changed the title ~~MAINT Remove loguniform fix, use scipy.stats instead~~ MAINT Remove loguniform fix, use scipy.stats instead, bump scipy version and Ubuntu version in CI Mar 23, 2023

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jeremiedbb mentioned this pull request Mar 24, 2023

MNT Remove sklearn.utils.fixes.loguniform #23730

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Veghit pushed a commit to Veghit/scikit-learn that referenced this pull request Apr 15, 2023

Remove loguniform fix, use scipy.stats instead (scikit-learn#24665)

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Co-authored-by: Olivier Grisel <[email protected]>

lorentzenchr mentioned this pull request Apr 30, 2023

Use scipy.stats.yeojohnson PowerTransformer #26308

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jeremiedbb mentioned this pull request May 25, 2023

RFC drop support for python 3.8 ? bump min dependencies ? #26438

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MAINT Remove loguniform fix, use scipy.stats instead, bump scipy version and Ubuntu version in CI #24665

MAINT Remove loguniform fix, use scipy.stats instead, bump scipy version and Ubuntu version in CI #24665

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MAINT Remove loguniform fix, use scipy.stats instead, bump scipy version and Ubuntu version in CI #24665

MAINT Remove loguniform fix, use scipy.stats instead, bump scipy version and Ubuntu version in CI #24665

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