BorgwardtLab
diff --git a/‎azure-pipelines.yml
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diff --git a/‎build_tools/azure/install.sh
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diff --git a/‎doc/conf.py
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diff --git a/‎doc/developers/contributing.rst
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diff --git a/‎doc/developers/maintainer.rst
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diff --git a/‎doc/modules/multiclass.rst
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diff --git a/‎doc/modules/svm.rst
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diff --git a/‎doc/whats_new/v0.22.rst
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diff --git a/‎sklearn/__init__.py
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diff --git a/‎sklearn/cluster/_agglomerative.py
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@@ -28,7 +28,7 @@ jobs:
           echo "Skipping linting"
           exit 0
         else
-          conda activate flake8_env
10000 +          source activate flake8_env
           ./build_tools/circle/linting.sh
         fi
       displayName: Run linting
 
@@ -97,24 +97,9 @@ elif [[ "$DISTRIB" == "conda-pip-latest" ]]; then
     make_conda "python=$PYTHON_VERSION"
     python -m pip install -U pip
     python -m pip install pytest==$PYTEST_VERSION pytest-cov pytest-xdist
-
-    # TODO: Remove pin when https://github.com/python-pillow/Pillow/issues/4518 gets fixed
-    python -m pip install "pillow>=4.3.0,!=7.1.0,!=7.1.1"
-
-    python -m pip install pandas matplotlib pyamg scikit-image
+    python -m pip install pandas matplotlib pyamg
     # do not install dependencies for lightgbm since it requires scikit-learn
     python -m pip install lightgbm --no-deps
-elif [[ "$DISTRIB" == "conda-pip-scipy-dev" ]]; then
-    make_conda "python=$PYTHON_VERSION"
-    python -m pip install -U pip
-    python -m pip install pytest==$PYTEST_VERSION pytest-cov pytest-xdist
-    echo "Installing numpy and scipy master wheels"
-    dev_url=https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com
-    pip install --pre --upgrade --timeout=60 -f $dev_url numpy scipy pandas cython
-    echo "Installing joblib master"
-    pip install https://github.com/joblib/joblib/archive/master.zip
-    echo "Installing pillow master"
-    pip install https://github.com/python-pillow/Pillow/archive/master.zip
 fi
 
 if [[ "$COVERAGE" == "true" ]]; then
 
@@ -314,7 +314,6 @@ def __call__(self, directory):
     },
     # avoid generating too many cross links
     'inspect_global_variables': False,
-    'remove_config_comments': True,
 }
 
 
 
@@ -264,8 +264,7 @@ modifying code and submitting a PR:
         $ git add modified_files
         $ git commit
 
-    to record your changes in Git, then push the changes to your GitHub
-    account with::
+       $ git push -u origin my_feature
 
        $ git push -u origin my_feature
 
 
@@ -114,11 +114,10 @@ Making a release
      page.
 
 2. On the branch for releasing, update the version number in
-   `sklearn/__init__.py`, the ``__version__`` variable by removing ``dev*``
-   only when ready to release. On master, increment the version in the same
-   place (when branching for release). This means while we're in the release
-   candidate period, the latest stable is two versions behind the master
-   branch, instead of one.
+   sklearn/__init__.py, the ``__version__`` variable by removing ``dev*`` only
+   when ready to release.
+   On master, increment the version in the same place (when branching for
+   release).
 
 3. At this point all relevant PRs should have been merged into the `0.99.X`
    branch. Create the source tarball:
 
@@ -62,14 +62,14 @@ regression is also supported.
   binary classif
F438
ication tasks, for example with
   :class:`sklearn.multioutput.MultiOutputClassifier`. This approach treats
   each label independently whereas multilabel classifiers *may* treat the
-  multiple classes simultaneously, accounting for correlated behavior among
+  multiple classes simultaneously, accounting for correlated behaviour amoung
   them.
 
   For example, prediction of the topics relevant to a text document or video.
   The document or video may be about one of 'religion', 'politics', 'finance'
   or 'education', several of the topic classes or all of the topic classes.
 
-  A valid representation of :term:`multilabel` `y` is an either dense or sparse
+  Valid representation of :term:`multilabel` `y` is either dense (or sparse)
   :term:`binary` matrix of shape ``(n_samples, n_classes)``. Each column
   represents a class. The ``1``'s in each row denote the positive classes a
   sample has been labelled with. An example of a dense matrix ``y`` for 3
@@ -99,10 +99,10 @@ regression is also supported.
 
   For example, prediction of both wind speed and wind direction, in degrees,
   using data obtained at a certain location. Each sample would be data
-  obtained at one location and both wind speed and direction would be
+  obtained at one location and both wind speed and directtion would be
   output for each sample.
 
-  A valid representation of :term:`multioutput` `y` is a dense matrix of shape
+  Valid representation of :term:`multilabel` `y` is dense matrix of shape
   ``(n_samples, n_classes)`` of floats. A column wise concatenation of
   :term:`continuous` variables. An example of ``y`` for 3 samples:
 
@@ -130,8 +130,8 @@ regression is also supported.
   image of a fruit, a label is output for both properties and each label is
   one of the possible classes of the corresponding property.
 
-  A valid representation of :term:`multioutput` `y` is a dense matrix of shape
-  ``(n_samples, n_classes)`` of class labels. A column wise concatenation of 1d
+  Valid representation of :term:`multilabel` `y` is dense matrix of shape
+  ``(n_samples, n_classes)`` of floats. A column wise concatenation of 1d
   :term:`multiclass` variables. An example of ``y`` for 3 samples:
 
     >>> y = np.array([['apple', 'green'], ['orange', 'orange'], ['pear', 'green']])
@@ -140,7 +140,7 @@ regression is also supported.
      ['orange' 'orange']
      ['pear' 'green']]
 
-  Note that all classifiers handling multioutput-multiclass (also known as
+  Note that any classifiers handling multioutput-multiclass (also known as
   multitask classification) tasks, support the multilabel classification task
   as a special case. Multitask classification is similar to the multioutput
   classification task with different model formulations. For more information,
 
@@ -277,12 +277,10 @@ with and without weight correction.
 
 :class:`SVC`, :class:`NuSVC`, :class:`SVR`, :class:`NuSVR`, :class:`LinearSVC`,
 :class:`LinearSVR` and :class:`OneClassSVM` implement also weights for
-individual samples in the `fit` method through the ``sample_weight`` parameter.
-Similar to ``class_weight``, this sets the parameter ``C`` for the i-th
-example to ``C * sample_weight[i]``, which will encourage the classifier to
-get these samples right. The figure below illustrates the effect of sample
-weighting on the decision boundary. The size of the circles is proportional
-to the sample weights:
+individual samples in method ``fit`` through keyword ``sample_weight``. Similar
+to ``class_weight``, these set the parameter ``C`` for the i-th example to
+``C * sample_weight[i]``.
+
 
 .. figure:: ../auto_examples/svm/images/sphx_glr_plot_weighted_samples_001.png
    :target: ../auto_examples/svm/plot_weighted_samples.html
 
@@ -2,53 +2,6 @@
 
 .. currentmodule:: sklearn
 
-.. _changes_0_22_2:
-
-Version 0.22.2.post1
-====================
-
-**March 3 2020**
-
-The 0.22.2.post1 release includes a packaging fix for the source distribution
-but the content of the packages is otherwise identical to the content of the
-wheels with the 0.22.2 version (without the .post1 suffix). Both contain the
-following changes.
-
-Changelog
----------
-
-:mod:`sklearn.impute`
-.....................
-
-- |Efficiency| Reduce :func:`impute.KNNImputer` asymptotic memory usage by
-  chunking pairwise distance computation.
-  :pr:`16397` by `Joel Nothman`_.
-
-:mod:`sklearn.metrics`
-......................
-
-- |Fix| Fixed a bug in :func:`metrics.plot_roc_curve` where
-  the name of the estimator was passed in the :class:`metrics.RocCurveDisplay`
-  instead of the parameter `name`. It results in a different plot when calling
-  :meth:`metrics.RocCurveDisplay.plot` for the subsequent times.
-  :pr:`16500` by :user:`Guillaume Lemaitre <glemaitre>`.
-
-- |Fix| Fixed a bug in :func:`metrics.plot_precision_recall_curve` where the
-  name of the estimator was passed in the
-  :class:`metrics.PrecisionRecallDisplay` instead of the parameter `name`. It
-  results in a different plot when calling
-  :meth:`metrics.PrecisionRecallDisplay.plot` for the subsequent times.
-  :pr:`16505` by :user:`Guillaume Lemaitre <glemaitre>`.
-
-:mod:`sklearn.neighbors`
-..............................
-
-- |Fix| Fix a bug which converted a list of arrays into a 2-D object 
-  array instead of a 1-D array containing NumPy arrays. This bug
-  was affecting :meth:`neighbors.NearestNeighbors.radius_neighbors`.
-  :pr:`16076` by :user:`Guillaume Lemaitre <glemaitre>` and  
-  :user:`Alex Shacked <alexshacked>`.
-
 .. _changes_0_22_1:
 
 Version 0.22.1
@@ -151,14 +104,6 @@ Changelog
   deprecated. This change is made to restore some backward compatibility with
   the behavior of this utility in version 0.21. :pr:`15947` by `Thomas Fan`_.
 
-:mod:`sklearn.multioutput`
-..........................
-
-- |Feature| :func:`multioutput.MultiOutputRegressor.fit` and
-  :func:`multioutput.MultiOutputClassifier.fit` now can accept `fit_params`
-  to pass to the `estimator.fit` method of each step. :issue:`15953`
-  :pr:`15959` by :user:`Ke Huang <huangk10>`.
-
 .. _changes_0_22:
 
 Version 0.22.0
 
@@ -39,7 +39,7 @@
 # Dev branch marker is: 'X.Y.dev' or 'X.Y.devN' where N is an integer.
 # 'X.Y.dev0' is the canonical version of 'X.Y.dev'
 #
-__version__ = '0.22'
+__version__ = '0.22.1'
 
 
 # On OSX, we can get a runtime error due to multiple OpenMP libraries loaded
 
@@ -21,6 +21,7 @@
 
 from . import _hierarchical_fast as _hierarchical
 from ._feature_agglomeration import AgglomerationTransform
+from ..utils import deprecated
 from ..utils._fast_dict import IntFloatDict
 from ..utils.fixes import _astype_copy_false
Original file line number	Diff line number	Diff line change
`@@ -314,7 +314,6 @@ def __call__(self, directory):`
`314`	`314`	`},`
`315`	`315`	`# avoid generating too many cross links`
`316`	`316`	`'inspect_global_variables': False,`
`317`		`- 'remove_config_comments': True,`
`318`	`317`	`}`
`319`	`318`
`320`	`319`
Original file line number	Diff line number	Diff line change
`@@ -39,7 +39,7 @@`
`39`	`39`	`# Dev branch marker is: 'X.Y.dev' or 'X.Y.devN' where N is an integer.`
`40`	`40`	`# 'X.Y.dev0' is the canonical version of 'X.Y.dev'`
`41`	`41`	`#`
`42`		`-__version__ = '0.22'`
	`42`	`+__version__ = '0.22.1'`
`43`	`43`
`44`	`44`
`45`	`45`	`# On OSX, we can get a runtime error due to multiple OpenMP libraries loaded`