MNT what's new corrections

Author: TomDLT

doc/whats_new/v0.20.rst

@@ -70,7 +70,7 @@ Changelog
 
 - |Fix| Fixed a regression in :class:`decomposition.IncrementalPCA` where
   0.20.0 raised an error if the number of samples in the final batch for
-   fitting IncrementalPCA was smaller than n_components.
+  fitting IncrementalPCA was smaller than n_components.
   :issue:`12234` by :user:`Ming Li <minggli>`.
 
 :mod:`sklearn.ensemble`
@@ -88,19 +88,18 @@ Changelog
 :mod:`sklearn.linear_model`
 ...........................
 
-- |Fix| :func:`linear_model.SGDClassifier` and variants
+- |Fix| :class:`linear_model.SGDClassifier` and variants
   with ``early_stopping=True`` would not use a consistent validation
   split in the multiclass case and this would cause a crash when using
   those estimators as part of parallel parameter search or cross-validation.
   :issue:`12122` by :user:`Olivier Grisel <ogrisel>`.
 
-- |Fix| Fixed a bug affecting :func:`SGDClassifier.fit` in the multiclass
+- |Fix| Fixed a bug affecting :class:`SGDClassifier` in the multiclass
   case. Each one-versus-all step is run in a :class:`joblib.Parallel` call and
   mutating a common parameter, causing a segmentation fault if called within a
   backend using processes and not threads. We now use ``require=sharedmem``
-  at the :class:`Parallel` instance creation.
-  :issue:`12518` by :user:`Pierre Glaser <pierreglaser>` and
-  :user:`Olivier Grisel <ogrisel>`.
+  at the :class:`joblib.Parallel` instance creation. :issue:`12518` by
+  :user:`Pierre Glaser <pierreglaser>` and :user:`Olivier Grisel <ogrisel>`.
 
 :mod:`sklearn.metrics`
 ......................
@@ -158,7 +157,7 @@ Miscellaneous
 - |Fix| Make sure to avoid raising ``FutureWarning`` when calling
   ``np.vstack`` with numpy 1.16 and later (use list comprehensions
   instead of generator expressions in many locations of the scikit-learn
-  code base). :issue:`12467` by :user:`Olivier Grisel`.
+  code base). :issue:`12467` by :user:`Olivier Grisel <ogrisel>`.
 
 .. _changes_0_20:
 
@@ -1032,7 +1031,7 @@ Support for Python 3.3 has been officially dropped.
   :issue:`9304` by :user:`Breno Freitas <brenolf>`.
 
 - |API| :class:`pipeline.FeatureUnion` now supports ``'drop'`` as a transformer
-  to drop features. :issue:`11144` by :user:`thomasjpfan`.
+  to drop features. :issue:`11144` by :user:`Thomas Fan <thomasjpfan>`.
 
 
 :mod:`sklearn.preprocessing`

doc/whats_new/v0.21.rst

@@ -40,57 +40,20 @@ Support for Python 3.4 and below has been officially dropped.
 - An entry goes here
 - An entry goes here
 
-:mod:`sklearn.linear_model`
-...........................
-- |Fix| Fixed a bug in :class:`linear_model.MultiTaskElasticNet` which was breaking
-  ``MultiTaskElasticNet`` and ``MultiTaskLasso`` when ``warm_start = True``. :issue:`12360`
-  by :user:`Aakanksha Joshi <joaak>`.
-
 :mod:`sklearn.cluster`
 ......................
 
 - |MajorFeature| A new clustering algorithm: :class:`cluster.OPTICS`: an
   algoritm related to :class:`cluster.DBSCAN`, that has hyperparameters easier
   to set and that scales better, by :user:`Shane <espg>`,
   :user:`Adrin Jalali <adrinjalali>`, and :user:`Erich Schubert <kno10>`.
-  
-:mod:`sklearn.preprocessing`
-............................
-
-- |Efficiency| Make :class:`preprocessing.MultiLabelBinarizer` to cache class mappings instead 
-  of calculating it every time on the fly.
-  :issue:`12116` by :user:`Ekaterina Krivich <kiote>` and `Joel Nothman`_.
-
-- |Efficiency| :class:`preprocessing.PolynomialFeatures` now supports compressed
-  sparse row (CSR) matrices as input for degrees 2 and 3. This is typically much
-  faster than the dense case as it scales with matrix density and expansion degree
-  (on the order of density^degree), and is much, much faster than the compressed
-  sparse column (CSC) case. :issue:`12197` by :user:`Andrew Nystrom <awnystrom>`.
 
-- |Efficiency| |API| Speed improvement in :class:`preprocessing.PolynomialFeatures`,
-  in the dense case. Also added a new parameter ``order`` which controls output
-  order for further speed performances. :issue:`12251` by `Tom Dupre la Tour`_.
-
-:mod:`sklearn.pipeline`
-.......................
-
-- |API| :class:`pipeline.Pipeline` now supports using ``'passthrough'`` as a
-  transformer. :issue:`11144` by :user:`thomasjpfan`.
-
-:mod:`sklearn.tree`
-...................
-- Decision Trees can now be plotted with matplotlib using
-  :func:`tree.export.plot_tree` without relying on  the ``dot`` library,
-  removing a hard-to-install dependency.
-  :issue:`8508` by `Andreas Müller`_.
-
-- |Feature| ``get_n_leaves()`` and ``get_depth()`` have been added to
-  :class:`tree.BaseDecisionTree` and consequently all estimators based
-  on it, including :class:`tree.DecisionTreeClassifier`,
-  :class:`tree.DecisionTreeRegressor`, :class:`tree.ExtraTreeClassifier`,
-  and :class:`tree.ExtraTreeRegressor`.
-  :issue:`12300` by :user:`Adrin Jalali <adrinjalali>`.
+:mod:`sklearn.linear_model`
+...........................
 
+- |Fix| Fixed a bug in :class:`linear_model.MultiTaskElasticNet` and
+  :class:`linear_model.MultiTaskLasso` which were breaking when
+  ``warm_start = True``. :issue:`12360` by :user:`Aakanksha Joshi <joaak>`.
 
 :mod:`sklearn.metrics`
 ......................
@@ -99,17 +62,14 @@ Support for Python 3.4 and below has been officially dropped.
   ``'max_error'`` scorer for single output regression.
   :issue:`12232` by :user:`Krishna Sangeeth <whiletruelearn>`.
 
-:mod:`sklearn.metrics`
-......................
-
 - |Feature| Add :func:`metrics.multilabel_confusion_matrix`, which calculates a
   confusion matrix with true positive, false positive, false negative and true
   negative counts for each class. This facilitates the calculation of set-wise
   metrics such as recall, specificity, fall out and miss rate.
   :issue:`11179` by :user:`Shangwu Yao <ShangwuYao>` and `Joel Nothman`_.
 
 :mod:`sklearn.neighbors`
-......................
+........................
 
 - |API| Methods in :class:`neighbors.NearestNeighbors` :
   :func:`~neighbors.NearestNeighbors.kneighbors`,
@@ -120,6 +80,42 @@ Support for Python 3.4 and below has been officially dropped.
   when called before fit :issue:`12279` by :user:`Krishna Sangeeth
   <whiletruelearn>`.
 
+:mod:`sklearn.pipeline`
+.......................
+
+- |API| :class:`pipeline.Pipeline` now supports using ``'passthrough'`` as a
+  transformer. :issue:`11144` by :user:`Thomas Fan <thomasjpfan>`.
+
+:mod:`sklearn.preprocessing`
+............................
+
+- |Efficiency| Make :class:`preprocessing.MultiLabelBinarizer` to cache class
+  mappings instead of calculating it every time on the fly.
+  :issue:`12116` by :user:`Ekaterina Krivich <kiote>` and `Joel Nothman`_.
+
+- |Efficiency| :class:`preprocessing.PolynomialFeatures` now supports compressed
+  sparse row (CSR) matrices as input for degrees 2 and 3. This is typically much
+  faster than the dense case as it scales with matrix density and expansion degree
+  (on the order of density^degree), and is much, much faster than the compressed
+  sparse column (CSC) case. :issue:`12197` by :user:`Andrew Nystrom <awnystrom>`.
+
+- |Efficiency| |API| Speed improvement in :class:`preprocessing.PolynomialFeatures`,
+  in the dense case. Also added a new parameter ``order`` which controls output
+  order for further speed performances. :issue:`12251` by `Tom Dupre la Tour`_.
+
+:mod:`sklearn.tree`
+...................
+- Decision Trees can now be plotted with matplotlib using
+  :func:`tree.export.plot_tree` without relying on the ``dot`` library,
+  removing a hard-to-install dependency. :issue:`8508` by `Andreas Müller`_.
+
+- |Feature| ``get_n_leaves()`` and ``get_depth()`` have been added to
+  :class:`tree.BaseDecisionTree` and consequently all estimators based
+  on it, including :class:`tree.DecisionTreeClassifier`,
+  :class:`tree.DecisionTreeRegressor`, :class:`tree.ExtraTreeClassifier`,
+  and :class:`tree.ExtraTreeRegressor`.
+  :issue:`12300` by :user:`Adrin Jalali <adrinjalali>`.
+
 Multiple modules
 ................
 
@@ -132,4 +128,4 @@ These changes mostly affect library developers.
   :func:`~utils.estimator_checks.check_estimator`, which checks that
   when `fit` is called twice with the same data, the ouput of
   `predit`, `predict_proba`, `transform`, and `decision_function` does not
-  change. :issue:`12328` by :user:`Nicolas Hug<NicolasHug>`
+  change. :issue:`12328` by :user:`Nicolas Hug <NicolasHug>`