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ReStructuredText
1072 lines
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ReStructuredText
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.. include:: _contributors.rst
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.. currentmodule:: sklearn
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.. _release_notes_0_24:
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============
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Version 0.24
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============
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For a short description of the main highlights of the release, please refer to
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:ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_0_24_0.py`.
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.. include:: changelog_legend.inc
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.. _changes_0_24_2:
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Version 0.24.2
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==============
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**April 2021**
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Changelog
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---------
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:mod:`sklearn.compose`
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......................
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- |Fix| `compose.ColumnTransformer.get_feature_names` does not call
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`get_feature_names` on transformers with an empty column selection.
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:pr:`19579` by `Thomas Fan`_.
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:mod:`sklearn.cross_decomposition`
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..................................
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- |Fix| Fixed a regression in :class:`cross_decomposition.CCA`. :pr:`19646`
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by `Thomas Fan`_.
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- |Fix| :class:`cross_decomposition.PLSRegression` raises warning for
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constant y residuals instead of a `StopIteration` error. :pr:`19922`
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by `Thomas Fan`_.
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:mod:`sklearn.decomposition`
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............................
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- |Fix| Fixed a bug in :class:`decomposition.KernelPCA`'s
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``inverse_transform``. :pr:`19732` by :user:`Kei Ishikawa <kstoneriv3>`.
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:mod:`sklearn.ensemble`
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.......................
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- |Fix| Fixed a bug in :class:`ensemble.HistGradientBoostingRegressor` `fit`
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with `sample_weight` parameter and `least_absolute_deviation` loss function.
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:pr:`19407` by :user:`Vadim Ushtanit <vadim-ushtanit>`.
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:mod:`sklearn.feature_extraction`
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.................................
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- |Fix| Fixed a bug to support multiple strings for a category when
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`sparse=False` in :class:`feature_extraction.DictVectorizer`.
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:pr:`19982` by :user:`Guillaume Lemaitre <glemaitre>`.
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:mod:`sklearn.gaussian_process`
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...............................
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- |Fix| Avoid explicitly forming inverse covariance matrix in
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:class:`gaussian_process.GaussianProcessRegressor` when set to output
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standard deviation. With certain covariance matrices this inverse is unstable
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to compute explicitly. Calling Cholesky solver mitigates this issue in
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computation.
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:pr:`19939` by :user:`Ian Halvic <iwhalvic>`.
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- |Fix| Avoid division by zero when scaling constant target in
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:class:`gaussian_process.GaussianProcessRegressor`. It was due to a std. dev.
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equal to 0. Now, such case is detected and the std. dev. is affected to 1
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avoiding a division by zero and thus the presence of NaN values in the
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normalized target.
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:pr:`19703` by :user:`sobkevich`, :user:`Boris Villazón-Terrazas <boricles>`
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and :user:`Alexandr Fonari <afonari>`.
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:mod:`sklearn.linear_model`
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...........................
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- |Fix|: Fixed a bug in :class:`linear_model.LogisticRegression`: the
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sample_weight object is not modified anymore. :pr:`19182` by
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:user:`Yosuke KOBAYASHI <m7142yosuke>`.
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:mod:`sklearn.metrics`
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......................
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- |Fix| :func:`metrics.top_k_accuracy_score` now supports multiclass
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problems where only two classes appear in `y_true` and all the classes
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are specified in `labels`.
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:pr:`19721` by :user:`Joris Clement <flyingdutchman23>`.
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:mod:`sklearn.model_selection`
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..............................
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- |Fix| :class:`model_selection.RandomizedSearchCV` and
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:class:`model_selection.GridSearchCV` now correctly shows the score for
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single metrics and verbose > 2. :pr:`19659` by `Thomas Fan`_.
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- |Fix| Some values in the `cv_results_` attribute of
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:class:`model_selection.HalvingRandomSearchCV` and
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:class:`model_selection.HalvingGridSearchCV` were not properly converted to
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numpy arrays. :pr:`19211` by `Nicolas Hug`_.
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- |Fix| The `fit` method of the successive halving parameter search
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(:class:`model_selection.HalvingGridSearchCV`, and
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:class:`model_selection.HalvingRandomSearchCV`) now correctly handles the
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`groups` parameter. :pr:`19847` by :user:`Xiaoyu Chai <xiaoyuchai>`.
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:mod:`sklearn.multioutput`
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..........................
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- |Fix| :class:`multioutput.MultiOutputRegressor` now works with estimators
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that dynamically define `predict` during fitting, such as
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:class:`ensemble.StackingRegressor`. :pr:`19308` by `Thomas Fan`_.
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:mod:`sklearn.preprocessing`
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............................
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- |Fix| Validate the constructor parameter `handle_unknown` in
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:class:`preprocessing.OrdinalEncoder` to only allow for `'error'` and
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`'use_encoded_value'` strategies.
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:pr:`19234` by `Guillaume Lemaitre <glemaitre>`.
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- |Fix| Fix encoder categories having dtype='S'
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:class:`preprocessing.OneHotEncoder` and
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:class:`preprocessing.OrdinalEncoder`.
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:pr:`19727` by :user:`Andrew Delong <andrewdelong>`.
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- |Fix| :meth:`preprocessing.OrdinalEncoder.transform` correctly handles
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unknown values for string dtypes. :pr:`19888` by `Thomas Fan`_.
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- |Fix| :meth:`preprocessing.OneHotEncoder.fit` no longer alters the `drop`
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parameter. :pr:`19924` by `Thomas Fan`_.
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:mod:`sklearn.semi_supervised`
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..............................
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- |Fix| Avoid NaN during label propagation in
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:class:`~sklearn.semi_supervised.LabelPropagation`.
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:pr:`19271` by :user:`Zhaowei Wang <ThuWangzw>`.
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:mod:`sklearn.tree`
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...................
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- |Fix| Fix a bug in `fit` of `tree.BaseDecisionTree` that caused
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segmentation faults under certain conditions. `fit` now deep copies the
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`Criterion` object to prevent shared concurrent accesses.
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:pr:`19580` by :user:`Samuel Brice <samdbrice>` and
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:user:`Alex Adamson <aadamson>` and
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:user:`Wil Yegelwel <wyegelwel>`.
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:mod:`sklearn.utils`
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....................
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- |Fix| Better contains the CSS provided by :func:`utils.estimator_html_repr`
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by giving CSS ids to the html representation. :pr:`19417` by `Thomas Fan`_.
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.. _changes_0_24_1:
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Version 0.24.1
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==============
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**January 2021**
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Packaging
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---------
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The 0.24.0 scikit-learn wheels were not working with MacOS <1.15 due to
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`libomp`. The version of `libomp` used to build the wheels was too recent for
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older macOS versions. This issue has been fixed for 0.24.1 scikit-learn wheels.
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Scikit-learn wheels published on PyPI.org now officially support macOS 10.13
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and later.
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Changelog
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---------
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:mod:`sklearn.metrics`
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......................
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- |Fix| Fix numerical stability bug that could happen in
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:func:`metrics.adjusted_mutual_info_score` and
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:func:`metrics.mutual_info_score` with NumPy 1.20+.
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:pr:`19179` by `Thomas Fan`_.
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:mod:`sklearn.semi_supervised`
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..............................
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- |Fix| :class:`semi_supervised.SelfTrainingClassifier` is now accepting
|
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meta-estimator (e.g. :class:`ensemble.StackingClassifier`). The validation
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of this estimator is done on the fitted estimator, once we know the existence
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of the method `predict_proba`.
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:pr:`19126` by :user:`Guillaume Lemaitre <glemaitre>`.
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.. _changes_0_24:
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Version 0.24.0
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==============
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**December 2020**
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Changed models
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--------------
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The following estimators and functions, when fit with the same data and
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parameters, may produce different models from the previous version. This often
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occurs due to changes in the modelling logic (bug fixes or enhancements), or in
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random sampling procedures.
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|
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- |Fix| :class:`decomposition.KernelPCA` behaviour is now more consistent
|
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between 32-bits and 64-bits data when the kernel has small positive
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eigenvalues.
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|
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- |Fix| :class:`decomposition.TruncatedSVD` becomes deterministic by exposing
|
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a `random_state` parameter.
|
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|
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- |Fix| :class:`linear_model.Perceptron` when `penalty='elasticnet'`.
|
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- |Fix| Change in the random sampling procedures for the center initialization
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of :class:`cluster.KMeans`.
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Details are listed in the changelog below.
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(While we are trying to better inform users by providing this information, we
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cannot assure that this list is complete.)
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Changelog
|
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---------
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:mod:`sklearn.base`
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...................
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- |Fix| :meth:`base.BaseEstimator.get_params` now will raise an
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`AttributeError` if a parameter cannot be retrieved as
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an instance attribute. Previously it would return `None`.
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:pr:`17448` by :user:`Juan Carlos Alfaro Jiménez <alfaro96>`.
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:mod:`sklearn.calibration`
|
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..........................
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- |Efficiency| :class:`calibration.CalibratedClassifierCV.fit` now supports
|
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parallelization via `joblib.Parallel` using argument `n_jobs`.
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:pr:`17107` by :user:`Julien Jerphanion <jjerphan>`.
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- |Enhancement| Allow :class:`calibration.CalibratedClassifierCV` use with
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prefit :class:`pipeline.Pipeline` where data is not `X` is not array-like,
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sparse matrix or dataframe at the start. :pr:`17546` by
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:user:`Lucy Liu <lucyleeow>`.
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- |Enhancement| Add `ensemble` parameter to
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:class:`calibration.CalibratedClassifierCV`, which enables implementation
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of calibration via an ensemble of calibrators (current method) or
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just one calibrator using all the data (similar to the built-in feature of
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:mod:`sklearn.svm` estimators with the `probabilities=True` parameter).
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:pr:`17856` by :user:`Lucy Liu <lucyleeow>` and
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:user:`Andrea Esuli <aesuli>`.
|
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|
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:mod:`sklearn.cluster`
|
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......................
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- |Enhancement| :class:`cluster.AgglomerativeClustering` has a new parameter
|
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`compute_distances`. When set to `True`, distances between clusters are
|
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computed and stored in the `distances_` attribute even when the parameter
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`distance_threshold` is not used. This new parameter is useful to produce
|
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dendrogram visualizations, but introduces a computational and memory
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overhead. :pr:`17984` by :user:`Michael Riedmann <mriedmann>`,
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:user:`Emilie Delattre <EmilieDel>`, and
|
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:user:`Francesco Casalegno <FrancescoCasalegno>`.
|
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- |Enhancement| :class:`cluster.SpectralClustering` and
|
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:func:`cluster.spectral_clustering` have a new keyword argument `verbose`.
|
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When set to `True`, additional messages will be displayed which can aid with
|
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debugging. :pr:`18052` by :user:`Sean O. Stalley <sstalley>`.
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- |Enhancement| Added :func:`cluster.kmeans_plusplus` as public function.
|
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Initialization by KMeans++ can now be called separately to generate
|
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initial cluster centroids. :pr:`17937` by :user:`g-walsh`
|
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|
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- |API| :class:`cluster.MiniBatchKMeans` attributes, `counts_` and
|
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`init_size_`, are deprecated and will be removed in 1.1 (renaming of 0.26).
|
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:pr:`17864` by :user:`Jérémie du Boisberranger <jeremiedbb>`.
|
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|
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|
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:mod:`sklearn.compose`
|
||
|
|
......................
|
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|
|
|
||
|
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- |Fix| :class:`compose.ColumnTransformer` will skip transformers the
|
||
|
|
column selector is a list of bools that are False. :pr:`17616` by
|
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`Thomas Fan`_.
|
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|
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|
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- |Fix| :class:`compose.ColumnTransformer` now displays the remainder in the
|
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|
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diagram display. :pr:`18167` by `Thomas Fan`_.
|
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|
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- |Fix| :class:`compose.ColumnTransformer` enforces strict count and order
|
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|
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of column names between `fit` and `transform` by raising an error instead
|
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of a warning, following the deprecation cycle.
|
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:pr:`18256` by :user:`Madhura Jayratne <madhuracj>`.
|
||
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|
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:mod:`sklearn.covariance`
|
||
|
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.........................
|
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|
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|
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- |API| Deprecates `cv_alphas_` in favor of `cv_results_['alphas']` and
|
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|
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`grid_scores_` in favor of split scores in `cv_results_` in
|
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:class:`covariance.GraphicalLassoCV`. `cv_alphas_` and `grid_scores_` will be
|
||
|
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removed in version 1.1 (renaming of 0.26).
|
||
|
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:pr:`16392` by `Thomas Fan`_.
|
||
|
|
|
||
|
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:mod:`sklearn.cross_decomposition`
|
||
|
|
..................................
|
||
|
|
|
||
|
|
- |Fix| Fixed a bug in :class:`cross_decomposition.PLSSVD` which would
|
||
|
|
sometimes return components in the reversed order of importance.
|
||
|
|
:pr:`17095` by `Nicolas Hug`_.
|
||
|
|
|
||
|
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- |Fix| Fixed a bug in :class:`cross_decomposition.PLSSVD`,
|
||
|
|
:class:`cross_decomposition.CCA`, and
|
||
|
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:class:`cross_decomposition.PLSCanonical`, which would lead to incorrect
|
||
|
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predictions for `est.transform(Y)` when the training data is single-target.
|
||
|
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:pr:`17095` by `Nicolas Hug`_.
|
||
|
|
|
||
|
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- |Fix| Increases the stability of :class:`cross_decomposition.CCA` :pr:`18746`
|
||
|
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by `Thomas Fan`_.
|
||
|
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|
||
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- |API| The bounds of the `n_components` parameter is now restricted:
|
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|
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- into `[1, min(n_samples, n_features, n_targets)]`, for
|
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:class:`cross_decomposition.PLSSVD`, :class:`cross_decomposition.CCA`,
|
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and :class:`cross_decomposition.PLSCanonical`.
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- into `[1, n_features]` or :class:`cross_decomposition.PLSRegression`.
|
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|
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An error will be raised in 1.1 (renaming of 0.26).
|
||
|
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:pr:`17095` by `Nicolas Hug`_.
|
||
|
|
|
||
|
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- |API| For :class:`cross_decomposition.PLSSVD`,
|
||
|
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:class:`cross_decomposition.CCA`, and
|
||
|
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:class:`cross_decomposition.PLSCanonical`, the `x_scores_` and `y_scores_`
|
||
|
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attributes were deprecated and will be removed in 1.1 (renaming of 0.26).
|
||
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They can be retrieved by calling `transform` on the training data.
|
||
|
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The `norm_y_weights` attribute will also be removed.
|
||
|
|
:pr:`17095` by `Nicolas Hug`_.
|
||
|
|
|
||
|
|
- |API| For :class:`cross_decomposition.PLSRegression`,
|
||
|
|
:class:`cross_decomposition.PLSCanonical`,
|
||
|
|
:class:`cross_decomposition.CCA`, and
|
||
|
|
:class:`cross_decomposition.PLSSVD`, the `x_mean_`, `y_mean_`, `x_std_`, and
|
||
|
|
`y_std_` attributes were deprecated and will be removed in 1.1
|
||
|
|
(renaming of 0.26).
|
||
|
|
:pr:`18768` by :user:`Maren Westermann <marenwestermann>`.
|
||
|
|
|
||
|
|
- |Fix| :class:`decomposition.TruncatedSVD` becomes deterministic by using the
|
||
|
|
`random_state`. It controls the weights' initialization of the underlying
|
||
|
|
ARPACK solver.
|
||
|
|
:pr:` #18302` by :user:`Gaurav Desai <gauravkdesai>` and
|
||
|
|
:user:`Ivan Panico <FollowKenny>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.datasets`
|
||
|
|
.......................
|
||
|
|
|
||
|
|
- |Feature| :func:`datasets.fetch_openml` now validates md5 checksum of arff
|
||
|
|
files downloaded or cached to ensure data integrity.
|
||
|
|
:pr:`14800` by :user:`Shashank Singh <shashanksingh28>` and `Joel Nothman`_.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`datasets.fetch_openml` now allows argument `as_frame`
|
||
|
|
to be 'auto', which tries to convert returned data to pandas DataFrame
|
||
|
|
unless data is sparse.
|
||
|
|
:pr:`17396` by :user:`Jiaxiang <fujiaxiang>`.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`datasets.fetch_covtype` now supports the optional
|
||
|
|
argument `as_frame`; when it is set to True, the returned Bunch object's
|
||
|
|
`data` and `frame` members are pandas DataFrames, and the `target` member is
|
||
|
|
a pandas Series.
|
||
|
|
:pr:`17491` by :user:`Alex Liang <tianchuliang>`.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`datasets.fetch_kddcup99` now supports the optional
|
||
|
|
argument `as_frame`; when it is set to True, the returned Bunch object's
|
||
|
|
`data` and `frame` members are pandas DataFrames, and the `target` member is
|
||
|
|
a pandas Series.
|
||
|
|
:pr:`18280` by :user:`Alex Liang <tianchuliang>` and
|
||
|
|
`Guillaume Lemaitre`_.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`datasets.fetch_20newsgroups_vectorized` now supports
|
||
|
|
loading as a pandas ``DataFrame`` by setting ``as_frame=True``.
|
||
|
|
:pr:`17499` by :user:`Brigitta Sipőcz <bsipocz>` and
|
||
|
|
`Guillaume Lemaitre`_.
|
||
|
|
|
||
|
|
- |API| The default value of `as_frame` in :func:`datasets.fetch_openml` is
|
||
|
|
changed from False to 'auto'.
|
||
|
|
:pr:`17610` by :user:`Jiaxiang <fujiaxiang>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.decomposition`
|
||
|
|
............................
|
||
|
|
|
||
|
|
- |API| For :class:`decomposition.NMF`,
|
||
|
|
the `init` value, when 'init=None' and
|
||
|
|
n_components <= min(n_samples, n_features) will be changed from
|
||
|
|
`'nndsvd'` to `'nndsvda'` in 1.1 (renaming of 0.26).
|
||
|
|
:pr:`18525` by :user:`Chiara Marmo <cmarmo>`.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`decomposition.FactorAnalysis` now supports the optional
|
||
|
|
argument `rotation`, which can take the value `None`, `'varimax'` or
|
||
|
|
`'quartimax'`. :pr:`11064` by :user:`Jona Sassenhagen <jona-sassenhagen>`.
|
||
|
|
|
||
|
|
- |Enhancement| :class:`decomposition.NMF` now supports the optional parameter
|
||
|
|
`regularization`, which can take the values `None`, 'components',
|
||
|
|
'transformation' or 'both', in accordance with
|
||
|
|
`decomposition.NMF.non_negative_factorization`.
|
||
|
|
:pr:`17414` by :user:`Bharat Raghunathan <bharatr21>`.
|
||
|
|
|
||
|
|
- |Fix| :class:`decomposition.KernelPCA` behaviour is now more consistent
|
||
|
|
between 32-bits and 64-bits data input when the kernel has small positive
|
||
|
|
eigenvalues. Small positive eigenvalues were not correctly discarded for
|
||
|
|
32-bits data.
|
||
|
|
:pr:`18149` by :user:`Sylvain Marié <smarie>`.
|
||
|
|
|
||
|
|
- |Fix| Fix :class:`decomposition.SparseCoder` such that it follows
|
||
|
|
scikit-learn API and support cloning. The attribute `components_` is
|
||
|
|
deprecated in 0.24 and will be removed in 1.1 (renaming of 0.26).
|
||
|
|
This attribute was redundant with the `dictionary` attribute and constructor
|
||
|
|
parameter.
|
||
|
|
:pr:`17679` by :user:`Xavier Dupré <sdpython>`.
|
||
|
|
|
||
|
|
- |Fix| :meth:`decomposition.TruncatedSVD.fit_transform` consistently returns
|
||
|
|
the same as :meth:`decomposition.TruncatedSVD.fit` followed by
|
||
|
|
:meth:`decomposition.TruncatedSVD.transform`.
|
||
|
|
:pr:`18528` by :user:`Albert Villanova del Moral <albertvillanova>` and
|
||
|
|
:user:`Ruifeng Zheng <zhengruifeng>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.discriminant_analysis`
|
||
|
|
....................................
|
||
|
|
|
||
|
|
- |Enhancement| :class:`discriminant_analysis.LinearDiscriminantAnalysis` can
|
||
|
|
now use custom covariance estimate by setting the `covariance_estimator`
|
||
|
|
parameter. :pr:`14446` by :user:`Hugo Richard <hugorichard>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.ensemble`
|
||
|
|
.......................
|
||
|
|
|
||
|
|
- |MajorFeature| :class:`ensemble.HistGradientBoostingRegressor` and
|
||
|
|
:class:`ensemble.HistGradientBoostingClassifier` now have native
|
||
|
|
support for categorical features with the `categorical_features`
|
||
|
|
parameter. :pr:`18394` by `Nicolas Hug`_ and `Thomas Fan`_.
|
||
|
|
|
||
|
|
- |Feature| :class:`ensemble.HistGradientBoostingRegressor` and
|
||
|
|
:class:`ensemble.HistGradientBoostingClassifier` now support the
|
||
|
|
method `staged_predict`, which allows monitoring of each stage.
|
||
|
|
:pr:`16985` by :user:`Hao Chun Chang <haochunchang>`.
|
||
|
|
|
||
|
|
- |Efficiency| break cyclic references in the tree nodes used internally in
|
||
|
|
:class:`ensemble.HistGradientBoostingRegressor` and
|
||
|
|
:class:`ensemble.HistGradientBoostingClassifier` to allow for the timely
|
||
|
|
garbage collection of large intermediate datastructures and to improve memory
|
||
|
|
usage in `fit`. :pr:`18334` by `Olivier Grisel`_ `Nicolas Hug`_, `Thomas
|
||
|
|
Fan`_ and `Andreas Müller`_.
|
||
|
|
|
||
|
|
- |Efficiency| Histogram initialization is now done in parallel in
|
||
|
|
:class:`ensemble.HistGradientBoostingRegressor` and
|
||
|
|
:class:`ensemble.HistGradientBoostingClassifier` which results in speed
|
||
|
|
improvement for problems that build a lot of nodes on multicore machines.
|
||
|
|
:pr:`18341` by `Olivier Grisel`_, `Nicolas Hug`_, `Thomas Fan`_, and
|
||
|
|
:user:`Egor Smirnov <SmirnovEgorRu>`.
|
||
|
|
|
||
|
|
- |Fix| Fixed a bug in
|
||
|
|
:class:`ensemble.HistGradientBoostingRegressor` and
|
||
|
|
:class:`ensemble.HistGradientBoostingClassifier` which can now accept data
|
||
|
|
with `uint8` dtype in `predict`. :pr:`18410` by `Nicolas Hug`_.
|
||
|
|
|
||
|
|
- |API| The parameter ``n_classes_`` is now deprecated in
|
||
|
|
:class:`ensemble.GradientBoostingRegressor` and returns `1`.
|
||
|
|
:pr:`17702` by :user:`Simona Maggio <simonamaggio>`.
|
||
|
|
|
||
|
|
- |API| Mean absolute error ('mae') is now deprecated for the parameter
|
||
|
|
``criterion`` in :class:`ensemble.GradientBoostingRegressor` and
|
||
|
|
:class:`ensemble.GradientBoostingClassifier`.
|
||
|
|
:pr:`18326` by :user:`Madhura Jayaratne <madhuracj>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.exceptions`
|
||
|
|
.........................
|
||
|
|
|
||
|
|
- |API| `exceptions.ChangedBehaviorWarning` and
|
||
|
|
`exceptions.NonBLASDotWarning` are deprecated and will be removed in
|
||
|
|
1.1 (renaming of 0.26).
|
||
|
|
:pr:`17804` by `Adrin Jalali`_.
|
||
|
|
|
||
|
|
:mod:`sklearn.feature_extraction`
|
||
|
|
.................................
|
||
|
|
|
||
|
|
- |Enhancement| :class:`feature_extraction.DictVectorizer` accepts multiple
|
||
|
|
values for one categorical feature. :pr:`17367` by :user:`Peng Yu <yupbank>`
|
||
|
|
and :user:`Chiara Marmo <cmarmo>`.
|
||
|
|
|
||
|
|
- |Fix| :class:`feature_extraction.text.CountVectorizer` raises an issue if a
|
||
|
|
custom token pattern which capture more than one group is provided.
|
||
|
|
:pr:`15427` by :user:`Gangesh Gudmalwar <ggangesh>` and
|
||
|
|
:user:`Erin R Hoffman <hoffm386>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.feature_selection`
|
||
|
|
................................
|
||
|
|
|
||
|
|
- |Feature| Added :class:`feature_selection.SequentialFeatureSelector`
|
||
|
|
which implements forward and backward sequential feature selection.
|
||
|
|
:pr:`6545` by `Sebastian Raschka`_ and :pr:`17159` by `Nicolas Hug`_.
|
||
|
|
|
||
|
|
- |Feature| A new parameter `importance_getter` was added to
|
||
|
|
:class:`feature_selection.RFE`, :class:`feature_selection.RFECV` and
|
||
|
|
:class:`feature_selection.SelectFromModel`, allowing the user to specify an
|
||
|
|
attribute name/path or a `callable` for extracting feature importance from
|
||
|
|
the estimator. :pr:`15361` by :user:`Venkatachalam N <venkyyuvy>`.
|
||
|
|
|
||
|
|
- |Efficiency| Reduce memory footprint in
|
||
|
|
:func:`feature_selection.mutual_info_classif`
|
||
|
|
and :func:`feature_selection.mutual_info_regression` by calling
|
||
|
|
:class:`neighbors.KDTree` for counting nearest neighbors. :pr:`17878` by
|
||
|
|
:user:`Noel Rogers <noelano>`.
|
||
|
|
|
||
|
|
- |Enhancement| :class:`feature_selection.RFE` supports the option for the
|
||
|
|
number of `n_features_to_select` to be given as a float representing the
|
||
|
|
percentage of features to select.
|
||
|
|
:pr:`17090` by :user:`Lisa Schwetlick <lschwetlick>` and
|
||
|
|
:user:`Marija Vlajic Wheeler <marijavlajic>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.gaussian_process`
|
||
|
|
...............................
|
||
|
|
|
||
|
|
- |Enhancement| A new method
|
||
|
|
`gaussian_process.kernel._check_bounds_params` is called after
|
||
|
|
fitting a Gaussian Process and raises a ``ConvergenceWarning`` if the bounds
|
||
|
|
of the hyperparameters are too tight.
|
||
|
|
:issue:`12638` by :user:`Sylvain Lannuzel <SylvainLan>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.impute`
|
||
|
|
.....................
|
||
|
|
|
||
|
|
- |Feature| :class:`impute.SimpleImputer` now supports a list of strings
|
||
|
|
when ``strategy='most_frequent'`` or ``strategy='constant'``.
|
||
|
|
:pr:`17526` by :user:`Ayako YAGI <yagi-3>` and
|
||
|
|
:user:`Juan Carlos Alfaro Jiménez <alfaro96>`.
|
||
|
|
|
||
|
|
- |Feature| Added method :meth:`impute.SimpleImputer.inverse_transform` to
|
||
|
|
revert imputed data to original when instantiated with
|
||
|
|
``add_indicator=True``. :pr:`17612` by :user:`Srimukh Sripada <d3b0unce>`.
|
||
|
|
|
||
|
|
- |Fix| replace the default values in :class:`impute.IterativeImputer`
|
||
|
|
of `min_value` and `max_value` parameters to `-np.inf` and `np.inf`,
|
||
|
|
respectively instead of `None`. However, the behaviour of the class does not
|
||
|
|
change since `None` was defaulting to these values already.
|
||
|
|
:pr:`16493` by :user:`Darshan N <DarshanGowda0>`.
|
||
|
|
|
||
|
|
- |Fix| :class:`impute.IterativeImputer` will not attempt to set the
|
||
|
|
estimator's `random_state` attribute, allowing to use it with more external classes.
|
||
|
|
:pr:`15636` by :user:`David Cortes <david-cortes>`.
|
||
|
|
|
||
|
|
- |Efficiency| :class:`impute.SimpleImputer` is now faster with `object` dtype array.
|
||
|
|
when `strategy='most_frequent'` in :class:`~sklearn.impute.SimpleImputer`.
|
||
|
|
:pr:`18987` by :user:`David Katz <DavidKatz-il>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.inspection`
|
||
|
|
.........................
|
||
|
|
|
||
|
|
- |Feature| :func:`inspection.partial_dependence` and
|
||
|
|
`inspection.plot_partial_dependence` now support calculating and
|
||
|
|
plotting Individual Conditional Expectation (ICE) curves controlled by the
|
||
|
|
``kind`` parameter.
|
||
|
|
:pr:`16619` by :user:`Madhura Jayratne <madhuracj>`.
|
||
|
|
|
||
|
|
- |Feature| Add `sample_weight` parameter to
|
||
|
|
:func:`inspection.permutation_importance`. :pr:`16906` by
|
||
|
|
:user:`Roei Kahny <RoeiKa>`.
|
||
|
|
|
||
|
|
- |API| Positional arguments are deprecated in
|
||
|
|
:meth:`inspection.PartialDependenceDisplay.plot` and will error in 1.1
|
||
|
|
(renaming of 0.26).
|
||
|
|
:pr:`18293` by `Thomas Fan`_.
|
||
|
|
|
||
|
|
:mod:`sklearn.isotonic`
|
||
|
|
.......................
|
||
|
|
|
||
|
|
- |Feature| Expose fitted attributes ``X_thresholds_`` and ``y_thresholds_``
|
||
|
|
that hold the de-duplicated interpolation thresholds of an
|
||
|
|
:class:`isotonic.IsotonicRegression` instance for model inspection purpose.
|
||
|
|
:pr:`16289` by :user:`Masashi Kishimoto <kishimoto-banana>` and
|
||
|
|
:user:`Olivier Grisel <ogrisel>`.
|
||
|
|
|
||
|
|
- |Enhancement| :class:`isotonic.IsotonicRegression` now accepts 2d array with
|
||
|
|
1 feature as input array. :pr:`17379` by :user:`Jiaxiang <fujiaxiang>`.
|
||
|
|
|
||
|
|
- |Fix| Add tolerance when determining duplicate X values to prevent
|
||
|
|
inf values from being predicted by :class:`isotonic.IsotonicRegression`.
|
||
|
|
:pr:`18639` by :user:`Lucy Liu <lucyleeow>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.kernel_approximation`
|
||
|
|
...................................
|
||
|
|
|
||
|
|
- |Feature| Added class :class:`kernel_approximation.PolynomialCountSketch`
|
||
|
|
which implements the Tensor Sketch algorithm for polynomial kernel feature
|
||
|
|
map approximation.
|
||
|
|
:pr:`13003` by :user:`Daniel López Sánchez <lopeLH>`.
|
||
|
|
|
||
|
|
- |Efficiency| :class:`kernel_approximation.Nystroem` now supports
|
||
|
|
parallelization via `joblib.Parallel` using argument `n_jobs`.
|
||
|
|
:pr:`18545` by :user:`Laurenz Reitsam <LaurenzReitsam>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.linear_model`
|
||
|
|
...........................
|
||
|
|
|
||
|
|
- |Feature| :class:`linear_model.LinearRegression` now forces coefficients
|
||
|
|
to be all positive when ``positive`` is set to ``True``.
|
||
|
|
:pr:`17578` by :user:`Joseph Knox <jknox13>`,
|
||
|
|
:user:`Nelle Varoquaux <NelleV>` and :user:`Chiara Marmo <cmarmo>`.
|
||
|
|
|
||
|
|
- |Enhancement| :class:`linear_model.RidgeCV` now supports finding an optimal
|
||
|
|
regularization value `alpha` for each target separately by setting
|
||
|
|
``alpha_per_target=True``. This is only supported when using the default
|
||
|
|
efficient leave-one-out cross-validation scheme ``cv=None``. :pr:`6624` by
|
||
|
|
:user:`Marijn van Vliet <wmvanvliet>`.
|
||
|
|
|
||
|
|
- |Fix| Fixes bug in :class:`linear_model.TheilSenRegressor` where
|
||
|
|
`predict` and `score` would fail when `fit_intercept=False` and there was
|
||
|
|
one feature during fitting. :pr:`18121` by `Thomas Fan`_.
|
||
|
|
|
||
|
|
- |Fix| Fixes bug in :class:`linear_model.ARDRegression` where `predict`
|
||
|
|
was raising an error when `normalize=True` and `return_std=True` because
|
||
|
|
`X_offset_` and `X_scale_` were undefined.
|
||
|
|
:pr:`18607` by :user:`fhaselbeck <fhaselbeck>`.
|
||
|
|
|
||
|
|
- |Fix| Added the missing `l1_ratio` parameter in
|
||
|
|
:class:`linear_model.Perceptron`, to be used when `penalty='elasticnet'`.
|
||
|
|
This changes the default from 0 to 0.15. :pr:`18622` by
|
||
|
|
:user:`Haesun Park <rickiepark>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.manifold`
|
||
|
|
.......................
|
||
|
|
|
||
|
|
- |Efficiency| Fixed :issue:`10493`. Improve Local Linear Embedding (LLE)
|
||
|
|
that raised `MemoryError` exception when used with large inputs.
|
||
|
|
:pr:`17997` by :user:`Bertrand Maisonneuve <bmaisonn>`.
|
||
|
|
|
||
|
|
- |Enhancement| Add `square_distances` parameter to :class:`manifold.TSNE`,
|
||
|
|
which provides backward compatibility during deprecation of legacy squaring
|
||
|
|
behavior. Distances will be squared by default in 1.1 (renaming of 0.26),
|
||
|
|
and this parameter will be removed in 1.3. :pr:`17662` by
|
||
|
|
:user:`Joshua Newton <joshuacwnewton>`.
|
||
|
|
|
||
|
|
- |Fix| :class:`manifold.MDS` now correctly sets its `_pairwise` attribute.
|
||
|
|
:pr:`18278` by `Thomas Fan`_.
|
||
|
|
|
||
|
|
:mod:`sklearn.metrics`
|
||
|
|
......................
|
||
|
|
|
||
|
|
- |Feature| Added :func:`metrics.cluster.pair_confusion_matrix` implementing
|
||
|
|
the confusion matrix arising from pairs of elements from two clusterings.
|
||
|
|
:pr:`17412` by :user:`Uwe F Mayer <ufmayer>`.
|
||
|
|
|
||
|
|
- |Feature| new metric :func:`metrics.top_k_accuracy_score`. It's a
|
||
|
|
generalization of :func:`metrics.top_k_accuracy_score`, the difference is
|
||
|
|
that a prediction is considered correct as long as the true label is
|
||
|
|
associated with one of the `k` highest predicted scores.
|
||
|
|
:func:`metrics.accuracy_score` is the special case of `k = 1`.
|
||
|
|
:pr:`16625` by :user:`Geoffrey Bolmier <gbolmier>`.
|
||
|
|
|
||
|
|
- |Feature| Added :func:`metrics.det_curve` to compute Detection Error Tradeoff
|
||
|
|
curve classification metric.
|
||
|
|
:pr:`10591` by :user:`Jeremy Karnowski <jkarnows>` and
|
||
|
|
:user:`Daniel Mohns <dmohns>`.
|
||
|
|
|
||
|
|
- |Feature| Added `metrics.plot_det_curve` and
|
||
|
|
:class:`metrics.DetCurveDisplay` to ease the plot of DET curves.
|
||
|
|
:pr:`18176` by :user:`Guillaume Lemaitre <glemaitre>`.
|
||
|
|
|
||
|
|
- |Feature| Added :func:`metrics.mean_absolute_percentage_error` metric and
|
||
|
|
the associated scorer for regression problems. :issue:`10708` fixed with the
|
||
|
|
PR :pr:`15007` by :user:`Ashutosh Hathidara <ashutosh1919>`. The scorer and
|
||
|
|
some practical test cases were taken from PR :pr:`10711` by
|
||
|
|
:user:`Mohamed Ali Jamaoui <mohamed-ali>`.
|
||
|
|
|
||
|
|
- |Feature| Added :func:`metrics.rand_score` implementing the (unadjusted)
|
||
|
|
Rand index.
|
||
|
|
:pr:`17412` by :user:`Uwe F Mayer <ufmayer>`.
|
||
|
|
|
||
|
|
- |Feature| `metrics.plot_confusion_matrix` now supports making colorbar
|
||
|
|
optional in the matplotlib plot by setting `colorbar=False`. :pr:`17192` by
|
||
|
|
:user:`Avi Gupta <avigupta2612>`
|
||
|
|
|
||
|
|
- |Enhancement| Add `sample_weight` parameter to
|
||
|
|
:func:`metrics.median_absolute_error`. :pr:`17225` by
|
||
|
|
:user:`Lucy Liu <lucyleeow>`.
|
||
|
|
|
||
|
|
- |Enhancement| Add `pos_label` parameter in
|
||
|
|
`metrics.plot_precision_recall_curve` in order to specify the positive
|
||
|
|
class to be used when computing the precision and recall statistics.
|
||
|
|
:pr:`17569` by :user:`Guillaume Lemaitre <glemaitre>`.
|
||
|
|
|
||
|
|
- |Enhancement| Add `pos_label` parameter in
|
||
|
|
`metrics.plot_roc_curve` in order to specify the positive
|
||
|
|
class to be used when computing the roc auc statistics.
|
||
|
|
:pr:`17651` by :user:`Clara Matos <claramatos>`.
|
||
|
|
|
||
|
|
- |Fix| Fixed a bug in
|
||
|
|
:func:`metrics.classification_report` which was raising AttributeError
|
||
|
|
when called with `output_dict=True` for 0-length values.
|
||
|
|
:pr:`17777` by :user:`Shubhanshu Mishra <napsternxg>`.
|
||
|
|
|
||
|
|
- |Fix| Fixed a bug in
|
||
|
|
:func:`metrics.classification_report` which was raising AttributeError
|
||
|
|
when called with `output_dict=True` for 0-length values.
|
||
|
|
:pr:`17777` by :user:`Shubhanshu Mishra <napsternxg>`.
|
||
|
|
|
||
|
|
- |Fix| Fixed a bug in
|
||
|
|
:func:`metrics.jaccard_score` which recommended the `zero_division`
|
||
|
|
parameter when called with no true or predicted samples.
|
||
|
|
:pr:`17826` by :user:`Richard Decal <crypdick>` and
|
||
|
|
:user:`Joseph Willard <josephwillard>`
|
||
|
|
|
||
|
|
- |Fix| bug in :func:`metrics.hinge_loss` where error occurs when
|
||
|
|
``y_true`` is missing some labels that are provided explicitly in the
|
||
|
|
``labels`` parameter.
|
||
|
|
:pr:`17935` by :user:`Cary Goltermann <Ultramann>`.
|
||
|
|
|
||
|
|
- |Fix| Fix scorers that accept a pos_label parameter and compute their metrics
|
||
|
|
from values returned by `decision_function` or `predict_proba`. Previously,
|
||
|
|
they would return erroneous values when pos_label was not corresponding to
|
||
|
|
`classifier.classes_[1]`. This is especially important when training
|
||
|
|
classifiers directly with string labeled target classes.
|
||
|
|
:pr:`18114` by :user:`Guillaume Lemaitre <glemaitre>`.
|
||
|
|
|
||
|
|
- |Fix| Fixed bug in `metrics.plot_confusion_matrix` where error occurs
|
||
|
|
when `y_true` contains labels that were not previously seen by the classifier
|
||
|
|
while the `labels` and `display_labels` parameters are set to `None`.
|
||
|
|
:pr:`18405` by :user:`Thomas J. Fan <thomasjpfan>` and
|
||
|
|
:user:`Yakov Pchelintsev <kyouma>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.model_selection`
|
||
|
|
..............................
|
||
|
|
|
||
|
|
- |MajorFeature| Added (experimental) parameter search estimators
|
||
|
|
:class:`model_selection.HalvingRandomSearchCV` and
|
||
|
|
:class:`model_selection.HalvingGridSearchCV` which implement Successive
|
||
|
|
Halving, and can be used as a drop-in replacements for
|
||
|
|
:class:`model_selection.RandomizedSearchCV` and
|
||
|
|
:class:`model_selection.GridSearchCV`. :pr:`13900` by `Nicolas Hug`_, `Joel
|
||
|
|
Nothman`_ and `Andreas Müller`_.
|
||
|
|
|
||
|
|
- |Feature| :class:`model_selection.RandomizedSearchCV` and
|
||
|
|
:class:`model_selection.GridSearchCV` now have the method ``score_samples``
|
||
|
|
:pr:`17478` by :user:`Teon Brooks <teonbrooks>` and
|
||
|
|
:user:`Mohamed Maskani <maskani-moh>`.
|
||
|
|
|
||
|
|
- |Enhancement| :class:`model_selection.TimeSeriesSplit` has two new keyword
|
||
|
|
arguments `test_size` and `gap`. `test_size` allows the out-of-sample
|
||
|
|
time series length to be fixed for all folds. `gap` removes a fixed number of
|
||
|
|
samples between the train and test set on each fold.
|
||
|
|
:pr:`13204` by :user:`Kyle Kosic <kykosic>`.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`model_selection.permutation_test_score` and
|
||
|
|
:func:`model_selection.validation_curve` now accept fit_params
|
||
|
|
to pass additional estimator parameters.
|
||
|
|
:pr:`18527` by :user:`Gaurav Dhingra <gxyd>`,
|
||
|
|
:user:`Julien Jerphanion <jjerphan>` and :user:`Amanda Dsouza <amy12xx>`.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`model_selection.cross_val_score`,
|
||
|
|
:func:`model_selection.cross_validate`,
|
||
|
|
:class:`model_selection.GridSearchCV`, and
|
||
|
|
:class:`model_selection.RandomizedSearchCV` allows estimator to fail scoring
|
||
|
|
and replace the score with `error_score`. If `error_score="raise"`, the error
|
||
|
|
will be raised.
|
||
|
|
:pr:`18343` by `Guillaume Lemaitre`_ and :user:`Devi Sandeep <dsandeep0138>`.
|
||
|
|
|
||
|
|
- |Enhancement| :func:`model_selection.learning_curve` now accept fit_params
|
||
|
|
to pass additional estimator parameters.
|
||
|
|
:pr:`18595` by :user:`Amanda Dsouza <amy12xx>`.
|
||
|
|
|
||
|
|
- |Fix| Fixed the `len` of :class:`model_selection.ParameterSampler` when
|
||
|
|
all distributions are lists and `n_iter` is more than the number of unique
|
||
|
|
parameter combinations. :pr:`18222` by `Nicolas Hug`_.
|
||
|
|
|
||
|
|
- |Fix| A fix to raise warning when one or more CV splits of
|
||
|
|
:class:`model_selection.GridSearchCV` and
|
||
|
|
:class:`model_selection.RandomizedSearchCV` results in non-finite scores.
|
||
|
|
:pr:`18266` by :user:`Subrat Sahu <subrat93>`,
|
||
|
|
:user:`Nirvan <Nirvan101>` and :user:`Arthur Book <ArthurBook>`.
|
||
|
|
|
||
|
|
- |Enhancement| :class:`model_selection.GridSearchCV`,
|
||
|
|
:class:`model_selection.RandomizedSearchCV` and
|
||
|
|
:func:`model_selection.cross_validate` support `scoring` being a callable
|
||
|
|
returning a dictionary of of multiple metric names/values association.
|
||
|
|
:pr:`15126` by `Thomas Fan`_.
|
||
|
|
|
||
|
|
:mod:`sklearn.multiclass`
|
||
|
|
.........................
|
||
|
|
|
||
|
|
- |Enhancement| :class:`multiclass.OneVsOneClassifier` now accepts
|
||
|
|
the inputs with missing values. Hence, estimators which can handle
|
||
|
|
missing values (may be a pipeline with imputation step) can be used as
|
||
|
|
a estimator for multiclass wrappers.
|
||
|
|
:pr:`17987` by :user:`Venkatachalam N <venkyyuvy>`.
|
||
|
|
|
||
|
|
- |Fix| A fix to allow :class:`multiclass.OutputCodeClassifier` to accept
|
||
|
|
sparse input data in its `fit` and `predict` methods. The check for
|
||
|
|
validity of the input is now delegated to the base estimator.
|
||
|
|
:pr:`17233` by :user:`Zolisa Bleki <zoj613>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.multioutput`
|
||
|
|
..........................
|
||
|
|
|
||
|
|
- |Enhancement| :class:`multioutput.MultiOutputClassifier` and
|
||
|
|
:class:`multioutput.MultiOutputRegressor` now accepts the inputs
|
||
|
|
with missing values. Hence, estimators which can handle missing
|
||
|
|
values (may be a pipeline with imputation step, HistGradientBoosting
|
||
|
|
estimators) can be used as a estimator for multiclass wrappers.
|
||
|
|
:pr:`17987` by :user:`Venkatachalam N <venkyyuvy>`.
|
||
|
|
|
||
|
|
- |Fix| A fix to accept tuples for the ``order`` parameter
|
||
|
|
in :class:`multioutput.ClassifierChain`.
|
||
|
|
:pr:`18124` by :user:`Gus Brocchini <boldloop>` and
|
||
|
|
:user:`Amanda Dsouza <amy12xx>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.naive_bayes`
|
||
|
|
..........................
|
||
|
|
|
||
|
|
- |Enhancement| Adds a parameter `min_categories` to
|
||
|
|
:class:`naive_bayes.CategoricalNB` that allows a minimum number of categories
|
||
|
|
per feature to be specified. This allows categories unseen during training
|
||
|
|
to be accounted for.
|
||
|
|
:pr:`16326` by :user:`George Armstrong <gwarmstrong>`.
|
||
|
|
|
||
|
|
- |API| The attributes ``coef_`` and ``intercept_`` are now deprecated in
|
||
|
|
:class:`naive_bayes.MultinomialNB`, :class:`naive_bayes.ComplementNB`,
|
||
|
|
:class:`naive_bayes.BernoulliNB` and :class:`naive_bayes.CategoricalNB`,
|
||
|
|
and will be removed in v1.1 (renaming of 0.26).
|
||
|
|
:pr:`17427` by :user:`Juan Carlos Alfaro Jiménez <alfaro96>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.neighbors`
|
||
|
|
........................
|
||
|
|
|
||
|
|
- |Efficiency| Speed up ``seuclidean``, ``wminkowski``, ``mahalanobis`` and
|
||
|
|
``haversine`` metrics in `neighbors.DistanceMetric` by avoiding
|
||
|
|
unexpected GIL acquiring in Cython when setting ``n_jobs>1`` in
|
||
|
|
:class:`neighbors.KNeighborsClassifier`,
|
||
|
|
:class:`neighbors.KNeighborsRegressor`,
|
||
|
|
:class:`neighbors.RadiusNeighborsClassifier`,
|
||
|
|
:class:`neighbors.RadiusNeighborsRegressor`,
|
||
|
|
:func:`metrics.pairwise_distances`
|
||
|
|
and by validating data out of loops.
|
||
|
|
:pr:`17038` by :user:`Wenbo Zhao <webber26232>`.
|
||
|
|
|
||
|
|
- |Efficiency| `neighbors.NeighborsBase` benefits of an improved
|
||
|
|
`algorithm = 'auto'` heuristic. In addition to the previous set of rules,
|
||
|
|
now, when the number of features exceeds 15, `brute` is selected, assuming
|
||
|
|
the data intrinsic dimensionality is too high for tree-based methods.
|
||
|
|
:pr:`17148` by :user:`Geoffrey Bolmier <gbolmier>`.
|
||
|
|
|
||
|
|
- |Fix| `neighbors.BinaryTree`
|
||
|
|
will raise a `ValueError` when fitting on data array having points with
|
||
|
|
different dimensions.
|
||
|
|
:pr:`18691` by :user:`Chiara Marmo <cmarmo>`.
|
||
|
|
|
||
|
|
- |Fix| :class:`neighbors.NearestCentroid` with a numerical `shrink_threshold`
|
||
|
|
will raise a `ValueError` when fitting on data with all constant features.
|
||
|
|
:pr:`18370` by :user:`Trevor Waite <trewaite>`.
|
||
|
|
|
||
|
|
- |Fix| In methods `radius_neighbors` and
|
||
|
|
`radius_neighbors_graph` of :class:`neighbors.NearestNeighbors`,
|
||
|
|
:class:`neighbors.RadiusNeighborsClassifier`,
|
||
|
|
:class:`neighbors.RadiusNeighborsRegressor`, and
|
||
|
|
:class:`neighbors.RadiusNeighborsTransformer`, using `sort_results=True` now
|
||
|
|
correctly sorts the results even when fitting with the "brute" algorithm.
|
||
|
|
:pr:`18612` by `Tom Dupre la Tour`_.
|
||
|
|
|
||
|
|
:mod:`sklearn.neural_network`
|
||
|
|
.............................
|
||
|
|
|
||
|
|
- |Efficiency| Neural net training and prediction are now a little faster.
|
||
|
|
:pr:`17603`, :pr:`17604`, :pr:`17606`, :pr:`17608`, :pr:`17609`, :pr:`17633`,
|
||
|
|
:pr:`17661`, :pr:`17932` by :user:`Alex Henrie <alexhenrie>`.
|
||
|
|
|
||
|
|
- |Enhancement| Avoid converting float32 input to float64 in
|
||
|
|
:class:`neural_network.BernoulliRBM`.
|
||
|
|
:pr:`16352` by :user:`Arthur Imbert <Henley13>`.
|
||
|
|
|
||
|
|
- |Enhancement| Support 32-bit computations in
|
||
|
|
:class:`neural_network.MLPClassifier` and
|
||
|
|
:class:`neural_network.MLPRegressor`.
|
||
|
|
:pr:`17759` by :user:`Srimukh Sripada <d3b0unce>`.
|
||
|
|
|
||
|
|
- |Fix| Fix method :meth:`neural_network.MLPClassifier.fit`
|
||
|
|
not iterating to ``max_iter`` if warm started.
|
||
|
|
:pr:`18269` by :user:`Norbert Preining <norbusan>` and
|
||
|
|
:user:`Guillaume Lemaitre <glemaitre>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.pipeline`
|
||
|
|
.......................
|
||
|
|
|
||
|
|
- |Enhancement| References to transformers passed through ``transformer_weights``
|
||
|
|
to :class:`pipeline.FeatureUnion` that aren't present in ``transformer_list``
|
||
|
|
will raise a ``ValueError``.
|
||
|
|
:pr:`17876` by :user:`Cary Goltermann <Ultramann>`.
|
||
|
|
|
||
|
|
- |Fix| A slice of a :class:`pipeline.Pipeline` now inherits the parameters of
|
||
|
|
the original pipeline (`memory` and `verbose`).
|
||
|
|
:pr:`18429` by :user:`Albert Villanova del Moral <albertvillanova>` and
|
||
|
|
:user:`Paweł Biernat <pwl>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.preprocessing`
|
||
|
|
............................
|
||
|
|
|
||
|
|
- |Feature| :class:`preprocessing.OneHotEncoder` now supports missing
|
||
|
|
values by treating them as a category. :pr:`17317` by `Thomas Fan`_.
|
||
|
|
|
||
|
|
- |Feature| Add a new ``handle_unknown`` parameter with a
|
||
|
|
``use_encoded_value`` option, along with a new ``unknown_value`` parameter,
|
||
|
|
to :class:`preprocessing.OrdinalEncoder` to allow unknown categories during
|
||
|
|
transform and set the encoded value of the unknown categories.
|
||
|
|
:pr:`17406` by :user:`Felix Wick <FelixWick>` and :pr:`18406` by
|
||
|
|
`Nicolas Hug`_.
|
||
|
|
|
||
|
|
- |Feature| Add ``clip`` parameter to :class:`preprocessing.MinMaxScaler`,
|
||
|
|
which clips the transformed values of test data to ``feature_range``.
|
||
|
|
:pr:`17833` by :user:`Yashika Sharma <yashika51>`.
|
||
|
|
|
||
|
|
- |Feature| Add ``sample_weight`` parameter to
|
||
|
|
:class:`preprocessing.StandardScaler`. Allows setting
|
||
|
|
individual weights for each sample. :pr:`18510` and
|
||
|
|
:pr:`18447` and :pr:`16066` and :pr:`18682` by
|
||
|
|
:user:`Maria Telenczuk <maikia>` and :user:`Albert Villanova <albertvillanova>`
|
||
|
|
and :user:`panpiort8` and :user:`Alex Gramfort <agramfort>`.
|
||
|
|
|
||
|
|
- |Enhancement| Verbose output of :class:`model_selection.GridSearchCV` has
|
||
|
|
been improved for readability. :pr:`16935` by :user:`Raghav Rajagopalan
|
||
|
|
<raghavrv>` and :user:`Chiara Marmo <cmarmo>`.
|
||
|
|
|
||
|
|
- |Enhancement| Add ``unit_variance`` to :class:`preprocessing.RobustScaler`,
|
||
|
|
which scales output data such that normally distributed features have a
|
||
|
|
variance of 1. :pr:`17193` by :user:`Lucy Liu <lucyleeow>` and
|
||
|
|
:user:`Mabel Villalba <mabelvj>`.
|
||
|
|
|
||
|
|
- |Enhancement| Add `dtype` parameter to
|
||
|
|
:class:`preprocessing.KBinsDiscretizer`.
|
||
|
|
:pr:`16335` by :user:`Arthur Imbert <Henley13>`.
|
||
|
|
|
||
|
|
- |Fix| Raise error on
|
||
|
|
:meth:`sklearn.preprocessing.OneHotEncoder.inverse_transform`
|
||
|
|
when `handle_unknown='error'` and `drop=None` for samples
|
||
|
|
encoded as all zeros. :pr:`14982` by
|
||
|
|
:user:`Kevin Winata <kwinata>`.
|
||
|
|
|
||
|
|
:mod:`sklearn.semi_supervised`
|
||
|
|
..............................
|
||
|
|
|
||
|
|
- |MajorFeature| Added :class:`semi_supervised.SelfTrainingClassifier`, a
|
||
|
|
meta-classifier that allows any supervised classifier to function as a
|
||
|
|
semi-supervised classifier that can learn from unlabeled data. :issue:`11682`
|
||
|
|
by :user:`Oliver Rausch <orausch>` and :user:`Patrice Becker <pr0duktiv>`.
|
||
|
|
|
||
|
|
- |Fix| Fix incorrect encoding when using unicode string dtypes in
|
||
|
|
:class:`preprocessing.OneHotEncoder` and
|
||
|
|
:class:`preprocessing.OrdinalEncoder`. :pr:`15763` by `Thomas Fan`_.
|
||
|
|
|
||
|
|
:mod:`sklearn.svm`
|
||
|
|
..................
|
||
|
|
|
||
|
|
- |Enhancement| invoke SciPy BLAS API for SVM kernel function in ``fit``,
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``predict`` and related methods of :class:`svm.SVC`, :class:`svm.NuSVC`,
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:class:`svm.SVR`, :class:`svm.NuSVR`, :class:`svm.OneClassSVM`.
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:pr:`16530` by :user:`Shuhua Fan <jim0421>`.
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:mod:`sklearn.tree`
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...................
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- |Feature| :class:`tree.DecisionTreeRegressor` now supports the new splitting
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criterion ``'poisson'`` useful for modeling count data. :pr:`17386` by
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:user:`Christian Lorentzen <lorentzenchr>`.
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- |Enhancement| :func:`tree.plot_tree` now uses colors from the matplotlib
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configuration settings. :pr:`17187` by `Andreas Müller`_.
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- |API| The parameter ``X_idx_sorted`` is now deprecated in
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:meth:`tree.DecisionTreeClassifier.fit` and
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:meth:`tree.DecisionTreeRegressor.fit`, and has not effect.
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:pr:`17614` by :user:`Juan Carlos Alfaro Jiménez <alfaro96>`.
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:mod:`sklearn.utils`
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....................
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- |Enhancement| Add ``check_methods_sample_order_invariance`` to
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:func:`~utils.estimator_checks.check_estimator`, which checks that
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estimator methods are invariant if applied to the same dataset
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with different sample order :pr:`17598` by :user:`Jason Ngo <ngojason9>`.
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- |Enhancement| Add support for weights in
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`utils.sparse_func.incr_mean_variance_axis`.
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By :user:`Maria Telenczuk <maikia>` and :user:`Alex Gramfort <agramfort>`.
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- |Fix| Raise ValueError with clear error message in :func:`utils.check_array`
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for sparse DataFrames with mixed types.
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:pr:`17992` by :user:`Thomas J. Fan <thomasjpfan>` and
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:user:`Alex Shacked <alexshacked>`.
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- |Fix| Allow serialized tree based models to be unpickled on a machine
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with different endianness.
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:pr:`17644` by :user:`Qi Zhang <qzhang90>`.
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- |Fix| Check that we raise proper error when axis=1 and the
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dimensions do not match in `utils.sparse_func.incr_mean_variance_axis`.
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By :user:`Alex Gramfort <agramfort>`.
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Miscellaneous
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.............
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- |Enhancement| Calls to ``repr`` are now faster
|
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when `print_changed_only=True`, especially with meta-estimators.
|
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:pr:`18508` by :user:`Nathan C. <Xethan>`.
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.. rubric:: Code and documentation contributors
|
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Thanks to everyone who has contributed to the maintenance and improvement of
|
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the project since version 0.23, including:
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Abo7atm, Adam Spannbauer, Adrin Jalali, adrinjalali, Agamemnon Krasoulis,
|
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Akshay Deodhar, Albert Villanova del Moral, Alessandro Gentile, Alex Henrie,
|
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Alex Itkes, Alex Liang, Alexander Lenail, alexandracraciun, Alexandre Gramfort,
|
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alexshacked, Allan D Butler, Amanda Dsouza, amy12xx, Anand Tiwari, Anderson
|
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Nelson, Andreas Mueller, Ankit Choraria, Archana Subramaniyan, Arthur Imbert,
|
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Ashutosh Hathidara, Ashutosh Kushwaha, Atsushi Nukariya, Aura Munoz, AutoViz
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and Auto_ViML, Avi Gupta, Avinash Anakal, Ayako YAGI, barankarakus,
|
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barberogaston, beatrizsmg, Ben Mainye, Benjamin Bossan, Benjamin Pedigo, Bharat
|
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Raghunathan, Bhavika Devnani, Biprateep Dey, bmaisonn, Bo Chang, Boris
|
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Villazón-Terrazas, brigi, Brigitta Sipőcz, Bruno Charron, Byron Smith, Cary
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Goltermann, Cat Chenal, CeeThinwa, chaitanyamogal, Charles Patel, Chiara Marmo,
|
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Christian Kastner, Christian Lorentzen, Christoph Deil, Christos Aridas, Clara
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Matos, clmbst, Coelhudo, crispinlogan, Cristina Mulas, Daniel López, Daniel
|
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Mohns, darioka, Darshan N, david-cortes, Declan O'Neill, Deeksha Madan,
|
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Elizabeth DuPre, Eric Fiegel, Eric Larson, Erich Schubert, Erin Khoo, Erin R
|
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Hoffman, eschibli, Felix Wick, fhaselbeck, Forrest Koch, Francesco Casalegno,
|
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Frans Larsson, Gael Varoquaux, Gaurav Desai, Gaurav Sheni, genvalen, Geoffrey
|
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Bolmier, George Armstrong, George Kiragu, Gesa Stupperich, Ghislain Antony
|
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Vaillant, Gim Seng, Gordon Walsh, Gregory R. Lee, Guillaume Chevalier,
|
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Guillaume Lemaitre, Haesun Park, Hannah Bohle, Hao Chun Chang, Harry Scholes,
|
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Harsh Soni, Henry, Hirofumi Suzuki, Hitesh Somani, Hoda1394, Hugo Le Moine,
|
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hugorichard, indecisiveuser, Isuru Fernando, Ivan Wiryadi, j0rd1smit, Jaehyun
|
||
|
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Ahn, Jake Tae, James Hoctor, Jan Vesely, Jeevan Anand Anne, JeroenPeterBos,
|
||
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JHayes, Jiaxiang, Jie Zheng, Jigna Panchal, jim0421, Jin Li, Joaquin
|
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Vanschoren, Joel Nothman, Jona Sassenhagen, Jonathan, Jorge Gorbe Moya, Joseph
|
||
|
|
Lucas, Joshua Newton, Juan Carlos Alfaro Jiménez, Julien Jerphanion, Justin
|
||
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Huber, Jérémie du Boisberranger, Kartik Chugh, Katarina Slama, kaylani2,
|
||
|
|
Kendrick Cetina, Kenny Huynh, Kevin Markham, Kevin Winata, Kiril Isakov,
|
||
|
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kishimoto, Koki Nishihara, Krum Arnaudov, Kyle Kosic, Lauren Oldja, Laurenz
|
||
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Reitsam, Lisa Schwetlick, Louis Douge, Louis Guitton, Lucy Liu, Madhura
|
||
|
|
Jayaratne, maikia, Manimaran, Manuel López-Ibáñez, Maren Westermann, Maria
|
||
|
|
Telenczuk, Mariam-ke, Marijn van Vliet, Markus Löning, Martin Scheubrein,
|
||
|
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Martina G. Vilas, Martina Megasari, Mateusz Górski, mathschy, mathurinm,
|
||
|
|
Matthias Bussonnier, Max Del Giudice, Michael, Milan Straka, Muoki Caleb, N.
|
||
|
|
Haiat, Nadia Tahiri, Ph. D, Naoki Hamada, Neil Botelho, Nicolas Hug, Nils
|
||
|
|
Werner, noelano, Norbert Preining, oj_lappi, Oleh Kozynets, Olivier Grisel,
|
||
|
|
Pankaj Jindal, Pardeep Singh, Parthiv Chigurupati, Patrice Becker, Pete Green,
|
||
|
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pgithubs, Poorna Kumar, Prabakaran Kumaresshan, Probinette4, pspachtholz,
|
||
|
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pwalchessen, Qi Zhang, rachel fischoff, Rachit Toshniwal, Rafey Iqbal Rahman,
|
||
|
|
Rahul Jakhar, Ram Rachum, RamyaNP, rauwuckl, Ravi Kiran Boggavarapu, Ray Bell,
|
||
|
|
Reshama Shaikh, Richard Decal, Rishi Advani, Rithvik Rao, Rob Romijnders, roei,
|
||
|
|
Romain Tavenard, Roman Yurchak, Ruby Werman, Ryotaro Tsukada, sadak, Saket
|
||
|
|
Khandelwal, Sam, Sam Ezebunandu, Sam Kimbinyi, Sarah Brown, Saurabh Jain, Sean
|
||
|
|
O. Stalley, Sergio, Shail Shah, Shane Keller, Shao Yang Hong, Shashank Singh,
|
||
|
|
Shooter23, Shubhanshu Mishra, simonamaggio, Soledad Galli, Srimukh Sripada,
|
||
|
|
Stephan Steinfurt, subrat93, Sunitha Selvan, Swier, Sylvain Marié, SylvainLan,
|
||
|
|
t-kusanagi2, Teon L Brooks, Terence Honles, Thijs van den Berg, Thomas J Fan,
|
||
|
|
Thomas J. Fan, Thomas S Benjamin, Thomas9292, Thorben Jensen, tijanajovanovic,
|
||
|
|
Timo Kaufmann, tnwei, Tom Dupré la Tour, Trevor Waite, ufmayer, Umberto Lupo,
|
||
|
|
Venkatachalam N, Vikas Pandey, Vinicius Rios Fuck, Violeta, watchtheblur, Wenbo
|
||
|
|
Zhao, willpeppo, xavier dupré, Xethan, Xue Qianming, xun-tang, yagi-3, Yakov
|
||
|
|
Pchelintsev, Yashika Sharma, Yi-Yan Ge, Yue Wu, Yutaro Ikeda, Zaccharie Ramzi,
|
||
|
|
zoj613, Zhao Feng.
|