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DOC Use Scientific Python Plausible instance for analytics #25547

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Merged
merged 3 commits into from
Apr 3, 2023

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lesteve
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@lesteve lesteve commented Feb 6, 2023

This switches analytics to https://views.scientific-python.org/ which is managed by Scientific Python. See scipy/scipy.org#435 for example, that added it for the scipy.org website and scipy/scipy#15401 that added it to docs.scipy.org

I asked via the Scientific Python Discord if this was fine to use it for scikit-learn and Stefan Van der Walt said it was. See this Discord message for more details.

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@lesteve
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lesteve commented Feb 6, 2023

That seems to work fine, clicking around in this PR doc I can see visits on https://views.scientific-python.org/scikit-learn.org

image

If you want to have a look at the dashboard:

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LGTM, great decision 😃

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ogrisel commented Feb 6, 2023

Thanks for moving forward with this @lesteve. While we are at it, I think we should be more transparent and add a section about this in our README.rst as scipy did.

BTW @tupui what is the load / cost of running this service? scikit-learn is typically averaging between 4.5 and 6.5 million monthly page views (depending on the season) in 2022. It's slowly growing over years but I wouldn't expect those numbers to double before at least a few more years (if ever).

/cc @francoisgoupil as he expressed interest about this topic in the past.

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tupui commented Feb 6, 2023

BTW @tupui what is the load / cost of running this service? scikit-learn is typically averaging between 4.5 and 6.5 million monthly page views (depending on the season) at the moment.

I don't know, this is question for @stefanv or @jarrodmillman 😃 Also interested to know and in general I am not sure how we are safe from things like DDOS.

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ogrisel commented Feb 6, 2023

@lesteve we should probably wait for the next scikit-learn monthly meeting before merging this PR (and add it to the agenda).

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stefanv commented Feb 6, 2023

Easiest way to know if the machine can handle the load is to try it. Calls should be async, so even if the server goes down it won't block loading of the site.

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Thank you @lesteve for putting this together! I am +1 on moving over to Plausible hosted by Scientific Python. As for the current Google Analytics data, I would want to export it somewhere just in case we need to reference it. If the dataset is too big, I'm okay with aggregating it. The historical number of active visitors is a common metric used to find funding.

With that in mind, I think it is important to backup the data on the Plausible instance, or at least export an aggregation of it. There is a Plausible API that we can query once a week to aggregate some data and place it on a public GitHub Repo. For the above use case, I think that would be good enough.

As for this PR, I prefer to turn analytics off on PRs. It would add more data into the database that is not useful.

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I also vote for us switching over to Plausible. If Numpy and Scipy are using it, I trust that we can consider it to be a good standard.

At this point in time, web analytics data is more of a nice to have. While it's useful to see where our userbase lies and how they like to interact with us, I don't consider it something we should pay for.

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stefanv commented Feb 7, 2023

As @thomasjpfan mentions, the database is not currently backed up. We have had to reset once before due to a plausible upgrade failure. If having reliable historic tracking is important to the project, I'd welcome help from someone with devops experience.

@lesteve
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lesteve commented Feb 8, 2023

If having reliable historic tracking is important to the project, I'd welcome help from someone with devops experience.

cc @norbusan since he asked, in our internal mailing list, what kind of help would be useful to make the Plausible instance more reliable. To be clear @norbusan I am not saying you should volunteer some time on this 😉.

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stefanv commented Feb 8, 2023

The instance is pretty reliable; we just don't have a backup procedure in place. I use backblaze to backup https://discuss.scientific-python.org, but there's only so much unpaid quota.

Here's an example of the type of issue I've run into before: plausible uses clickhouse as an events database. After an upgrade, a table is corrupted. Running a SELECT on the table gives some hideous internal error, and Googling for that error just makes you feel lonely.

So, yes, you could probably create a DB from scratch and populate it from the old volume, using Yandex's outdated Clickhouse client Docker image and praying everything holds together. But that's the kind of effort I don't want you to expect, unless a volunteer steps up.

@tupui
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tupui commented Feb 8, 2023

It should just be a simple dump no? I am not familiar with ClickHouse but when I setup a Postgres DB this is one of the first thing I set in the background, a dump/restore strategy. It's simple, a bit slow but still the recommended way to backup.

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Thank you for initiating this, @lesteve.

I think having a way to understand the webpages people browse has high value for scikit-learn. I have enough work to do for scikit-learn already and I trust people for taking the best decisions regarding canary-migrating from Google Analytics.

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stefanv commented Feb 8, 2023

It should just be a simple dump no? I am not familiar with ClickHouse but when I setup a Postgres DB this is one of the first thing I set in the background, a dump/restore strategy. It's simple, a bit slow but still the recommended way to backup.

Backing up the (two) databases is not hard, it just needs to be done. I.e., set up a cron job and find a place to put the data.

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It should just be a simple dump no? I am not familiar with ClickHouse but when I setup a Postgres DB this is one of the first thing I set in the background, a dump/restore strategy. It's simple, a bit slow but still the recommended way to backup.

Backing up the (two) databases is not hard, it just needs to be done. I.e., set up a cron job and find a place to put the data.

How big the databases are as dumps?

Considering other analytics options that require in the hundreds of EUR/USD per month, a backup to backblaze/aws/gcp should be far less problematic.

@lesteve
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lesteve commented Mar 20, 2023

I haved added this PR as a topic in the next scikit-learn developer meeting.

I have also kept Google Analytics for now since I had some feed-back that keeping both for some time may be a good idea.

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+1 for keeping both at least for a few months.

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ogrisel commented Apr 1, 2023

I think we have a consensus on merging this as it was discussed at the last meeting and nobody expressed objections. Let's merge this at the beginning of next week not to put unnecessary ops pressure on the server admins on a WE :)

@betatim betatim merged commit 9202cea into scikit-learn:main Apr 3, 2023
@lesteve lesteve deleted the plausible-analytics branch April 3, 2023 09:10
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ogrisel commented Apr 4, 2023

I connected today and so far I see very few hits on https://views.scientific-python.org/scikit-learn.org:

image

But at this point, the plausible tracker is only deployed on the /dev/ subtree of the website. I tried to compare with the numbers from the GA tracker on the /dev/ subtree but unfortunately I cannot get those numbers on an hourly resolution (only daily). So we need to wait for a few days.

On GA we typically get between 0.5k and 2k pageviews on the /dev/ subtree while we get between 120k and 220k on the /stable/ subtree.

@lesteve
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lesteve commented Apr 12, 2023

I had a quick look comparing Plausible and Google Analytics. I used the same date range 5 April - 11 April:
image

image

The number are not too far but are not super close either. I guess there are implementation details that differ and we should not expect an exact match, for example see https://plausible.io/vs-google-analytics#avoiding-the-adblockers.

Is this good enough to try and use Plausible on the stable website? If so, I will open a PR targetting the 1.2.X branch.

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betatim commented Apr 12, 2023

I'd vote for "close enough". Maybe with it being on stable we get more statistics and can see that the gaps get smaller (as a fraction). For example the sorting of which pages are visited most should become more stable. I think right now the order doesn't match up very well for the lower "top ten" but that is because it is small statistics.

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lesteve commented Apr 12, 2023

Sounds good, I have opened #26160 to backport this PR in the 1.2.X branch.

Veghit pushed a commit to Veghit/scikit-learn that referenced this pull request Apr 15, 2023
MohitBurkule added a commit to MohitBurkule/scikit-learn that referenced this pull request May 7, 2023
* 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)

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* MAINT Added Parameter Validation for datasets.make_circles (scikit-learn#25848)

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* MNT use a single job by default with sphinx build (scikit-learn#25836)

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* MAINT parameter validation for sklearn.datasets.fetch_lfw_people (scikit-learn#25820)

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* 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)

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* MAINT Ensure disjoint interval constraints (scikit-learn#25797)

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* TST use global_random_seed in test_gpc.py (scikit-learn#24600)

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* 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)

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* 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)

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Co-authored-by: Jovan Stojanovic <62058944+jovan-stojanovic@users.noreply.github.com>
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* CI make it possible to cancel running Azure jobs (scikit-learn#25876)

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* 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)

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* MAINT Parameters validation for metrics.ndcg_score (scikit-learn#25885)

* ENH KMeans initialization account for sample weights (scikit-learn#25752)

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* 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)

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* MAINT validate_params for plot_tree (scikit-learn#25882)

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* MAINT add missing space in error message in SVM (scikit-learn#25913)

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* 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)

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* 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)

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* TST Speed-up test_partial_dependence.test_output_shape (scikit-learn#25895)

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* MAINT Parameters validation for datasets.make_regression (scikit-learn#25899)

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* 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)

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Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>

* 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)

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* 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)

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* MAINT Clean-up deprecated max_features="auto" in trees/forests/gb (scikit-learn#25941)

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* MAINT Clean-up remaining SGDClassifier(loss="log") (scikit-learn#25938)

* FIX Fixes pandas extension arrays in check_array (scikit-learn#25813)

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* 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)

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* 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)

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* FIX improve error message when computing NDCG with a single document (scikit-learn#25672)

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* MAINT introduce _get_response_values and _check_response_methods (scikit-learn#23073)

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* MAINT Extend message for large sparse matrices support (scikit-learn#25961)

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* MAINT Parameters validation for datasets.make_gaussian_quantiles (scikit-learn#25959)

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* 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)

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* 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)

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* 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)

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* FIX SequentialFeatureSelector throws IndexError when cv is a generator (scikit-learn#25973)

* ENH Adds infrequent categories support to OrdinalEncoder (scikit-learn#25677)

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* 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 <git@jjerphan.xyz>

* 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 <g.lemaitre58@gmail.com>

* 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)

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Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

* API Replace `n_iter` in `Bayesian Ridge` and `ARDRegression` (scikit-learn#25697)

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* 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)

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* ENH Adds isdtype to Array API wrapper (scikit-learn#26029)

* MAINT Parameters validation for sklearn.metrics.silhouette_score (scikit-learn#26054)

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* MAINT Parameters validation for sklearn.metrics.pairwise.cosine_distances (scikit-learn#26046)

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* 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)

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* MAINT Parameters validation for sklearn.preprocessing.label_binarize (scikit-learn#26078)

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* MAINT parameter validation for d2_absolute_error_score (scikit-learn#26066)

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* MAINT Parameter validation for roc_auc_score (scikit-learn#26007)

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* MAINT Parameters validation for sklearn.preprocessing.normalize (scikit-learn#26069)

Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>

* MAINT Parameter validation for metrics.cluster.fowlkes_mallows_score (scikit-learn#26080)

Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>

* MAINT Parameters validation for compose.make_column_transformer (scikit-learn#25897)

Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>

* MAINT Parameters validation for sklearn.metrics.pairwise.polynomial_kernel (scikit-learn#26070)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.metrics.pairwise.rbf_kernel (scikit-learn#26071)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.metrics.pairwise.sigmoid_kernel (scikit-learn#26072)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* 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 <git@jjerphan.xyz>
Co-authored-by: Tim Head <betatim@gmail.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.metrics.cluster.homogeneity_completeness_v_measure (scikit-learn#26137)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.metrics.rand_score (scikit-learn#26138)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* 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 <thomasjpfan@gmail.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.datasets.load_breast_cancer (scikit-learn#26165)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* ASV Fix tol in SGDRegressorBenchmark (scikit-learn#26146)

Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>

* 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 <git@jjerphan.xyz>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>

* MAINT Parameters validation for sklearn.neighbors.sort_graph_by_row_values (scikit-learn#26173)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* FIX improve convergence criterion for LogisticRegression(penalty="l1", solver='liblinear') (scikit-learn#25214)

Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

* 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 <g.lemaitre58@gmail.com>
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* 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 <g.lemaitre58@gmail.com>
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.datasets.load_digits (scikit-learn#26195)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.preprocessing.quantile_transform (scikit-learn#26144)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.model_selection.cross_validate (scikit-learn#26129)

Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>

* DOC Adds TargetEncoder example explaining the internal CV (scikit-learn#26185)

Co-authored-by: Tim Head <betatim@gmail.com>

* spelling mistake corrected in documentation for script `plot_document_clustering.py` (scikit-learn#26228)

Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

* FIX possible UnboundLocalError in fetch_openml (scikit-learn#26236)

* ENH Adds PyTorch support to LinearDiscriminantAnalysis (scikit-learn#25956)

Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Co-authored-by: Tim Head <betatim@gmail.com>

* 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 <thomasjpfan@gmail.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.datasets.load_files (scikit-learn#26203)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.datasets.get_data_home (scikit-learn#26260)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* 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 <jeremiedbb@yahoo.fr>

* MAINT Parameters validation for sklearn.inspection.partial_dependence (scikit-learn#26209)

Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>

* MAINT Parameters validation for sklearn.model_selection.validation_curve (scikit-learn#26229)

Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

* MAINT Parameters validation for sklearn.model_selection.learning_curve (scikit-learn#26227)

Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>

* 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 <34657725+jeremiedbb@users.noreply.github.com>

* MNT Improve error message when checking classification target is of a non-regression type (scikit-learn#26281)

Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>

* 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 <betatim@gmail.com>
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>

* 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 <34657725+jeremiedbb@users.noreply.github.com>
Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com>

* DOC Add HGBDT to "see also" section of random forests (scikit-learn#26319)

Co-authored-by: ArturoAmorQ <arturo.amor-quiroz@polytechnique.edu>
Co-authored-by: Tim Head <betatim@gmail.com>

* 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 <olivier.grisel@ensta.org>

* ENH Allow for appropriate dtype us in `preprocessing.PolynomialFeatures` for sparse matrices (scikit-learn#23731)

Co-authored-by: Aleksandr Kokhaniukov <alexander.kohanyukov@gmail.com>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>

* DOC Fix minor typo (scikit-learn#26327)

* MAINT bump minimum version for pytest (scikit-learn#26184)

Co-authored-by: Loïc Estève <loic.esteve@ymail.com>
Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

* 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 <g.lemaitre58@gmail.com>

* FIX make pipeline pass check_estimator (scikit-learn#26325)

* FEA Add multiclass support to `average_precision_score` (scikit-learn#24769)

Co-authored-by: Geoffrey <geoffrey.bolmier@gmail.com>
Co-authored-by: gbolmier <geoffrey.bolmier@volvocars.com>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>

---------

Signed-off-by: Julien Jerphanion <git@jjerphan.xyz>
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>
Co-authored-by: Meekail Zain <34613774+Micky774@users.noreply.github.com>
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
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Co-authored-by: zeeshan lone <56621467+still-learning-ev@users.noreply.github.com>
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