.. _changes_1_1_2:

Version 1.1.2

**In Development**

Changelog

:mod:`sklearn.cluster`

- |Fix| Fixed a bug in :class:`cluster.Birch` that could trigger an error when splitting

a node if there are duplicates in the dataset.

:pr:`23395` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

.. _changes_1_1_1:

Version 1.1.1

**May 2022**

Changelog

- |Enhancement| The error message is improved when importing

:class:`model_selection.HalvingGridSearchCV`,

:class:`model_selection.HalvingRandomSearchCV`, or

:class:`impute.IterativeImputer` without importing the experimental flag.

:pr:`23194` by `Thomas Fan`_.

- |Enhancement| Added an extension in doc/conf.py to automatically generate

the list of estimators that handle NaN values.

:pr:`23198` by :user:`Lise Kleiber <lisekleiber>`, :user:`Zhehao Liu <MaxwellLZH>`

and :user:`Chiara Marmo <cmarmo>`.

:mod:`sklearn.datasets`

- |Fix| Avoid timeouts in :func:`datasets.fetch_openml` by not passing a

`timeout` argument, :pr:`23358` by :user:`Loïc Estève <lesteve>`.

:mod:`sklearn.decomposition`

- |Fix| Avoid spurious warning in :class:`decomposition.IncrementalPCA` when

`n_samples == n_components`. :pr:`23264` by :user:`Lucy Liu <lucyleeow>`.

:mod:`sklearn.feature_selection`

- |Fix| The `partial_fit` method of :class:`feature_selection.SelectFromModel`

now conducts validation for `max_features` and `feature_names_in` parameters.

:pr:`23299` by :user:`Long Bao <lorentzbao>`.

:mod:`sklearn.metrics`

- |Fix| Fixes :func:`metrics.precision_recall_curve` to compute precision-recall at 100%

recall. The Precision-Recall curve now displays the last point corresponding to a

classifier that always predicts the positive class: recall=100% and

precision=class balance.

:pr:`23214` by :user:`Stéphane Collot <stephanecollot>` and :user:`Max Baak <mbaak>`.

:mod:`sklearn.preprocessing`

- |Fix| :class:`preprocessing.PolynomialFeatures` with ``degree`` equal to 0

will raise error when ``include_bias`` is set to False, and outputs a single

constant array when ``include_bias`` is set to True.

:pr:`23370` by :user:`Zhehao Liu <MaxwellLZH>`.

:mod:`sklearn.tree`

- |Fix| Fixes performance regression with low cardinality features for

:class:`tree.DecisionTreeClassifier`,

:class:`tree.DecisionTreeRegressor`,

:class:`ensemble.RandomForestClassifier`,

:class:`ensemble.RandomForestRegressor`,

:class:`ensemble.GradientBoostingClassifier`, and

:class:`ensemble.GradientBoostingRegressor`.

:pr:`23410` by :user:`Loïc Estève <lesteve>`.

:mod:`sklearn.utils`

- |Fix| :func:`utils.class_weight.compute_sample_weight` now works with sparse `y`.

:pr:`23115` by :user:`kernc <kernc>`.

- |Enhancement| Removes random unique identifiers in the HTML representation.

With this change, jupyter notebooks are reproducible as long as the cells are

run in the same order. :pr:`23098` by `Thomas Fan`_.

- |Fix| Estimators with `non_deterministic` tag set to `True` will skip both

`check_methods_sample_order_invariance` and `check_methods_subset_invariance` tests.

:pr:`22318` by :user:`Zhehao Liu <MaxwellLZH>`.

- |API| The option for using the log loss, aka binomial or multinomial deviance, via

the `loss` parameters was made more consistent. The preferred way is by

setting the value to `"log_loss"`. Old option names are still valid and

produce the same models, but are deprecated and will be removed in version

1.3.

- For :class:`ensemble.GradientBoostingClassifier`, the `loss` parameter name

"deviance" is deprecated in favor of the new name "log_loss", which is now the

default.

:pr:`23036` by :user:`Christian Lorentzen <lorentzenchr>`.

- For :class:`ensemble.HistGradientBoostingClassifier`, the `loss` parameter names

"auto", "binary_crossentropy" and "categorical_crossentropy" are deprecated in

favor of the new name "log_loss", which is now the default.

:pr:`23040` by :user:`Christian Lorentzen <lorentzenchr>`.

- For :class:`linear_model.SGDClassifier`, the `loss` parameter name

"log" is deprecated in favor of the new name "log_loss".

:pr:`23046` by :user:`Christian Lorentzen <lorentzenchr>`.

- |API| Rich html representation of estimators is now enabled by default in Jupyter

notebooks. It can be deactivated by setting `display='text'` in

:func:`sklearn.set_config`.

:pr:`22856` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

2357juan, Abhishek Gupta, adamgonzo, Adam Li, adijohar, Aditya Kumawat, Aditya

Raghuwanshi, Aditya Singh, Adrian Trujillo Duron, Adrin Jalali, ahmadjubair33,

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Ritter, christopherlim98, Christoph T. Weidemann, Christos Aridas, Claudio

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Dave Eargle, David Gilbertson, David Poznik, Dea María Léon, Dennis Osei,

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