scikit-learn · thomasjpfan · May 8, 2019 · Mar 1, 2019 · Mar 8, 2019 · Mar 15, 2019
diff --git a/doc/modules/linear_model.rst b/doc/modules/linear_model.rst
@@ -136,17 +136,24 @@ Setting the regularization parameter: generalized Cross-Validation
 ------------------------------------------------------------------
 
 :class:`RidgeCV` implements ridge regression with built-in
-cross-validation of the alpha parameter.  The object works in the same way
+cross-validation of the alpha parameter. The object works in the same way
 as GridSearchCV except that it defaults to Generalized Cross-Validation
 (GCV), an efficient form of leave-one-out cross-validation::
 
+    >>> import numpy as np
     >>> from sklearn import linear_model
-    >>> reg = linear_model.RidgeCV(alphas=[0.1, 1.0, 10.0], cv=3)
-    >>> reg.fit([[0, 0], [0, 0], [1, 1]], [0, .1, 1])       # doctest: +SKIP
-    RidgeCV(alphas=[0.1, 1.0, 10.0], cv=3, fit_intercept=True, scoring=None,
-        normalize=False)
-    >>> reg.alpha_                                      # doctest: +SKIP
-    0.1
+    >>> reg = linear_model.RidgeCV(alphas=np.logspace(-6, 6, 13))
+    >>> reg.fit([[0, 0], [0, 0], [1, 1]], [0, .1, 1])       # doctest: +NORMALIZE_WHITESPACE
+    RidgeCV(alphas=array([1.e-06, 1.e-05, 1.e-04, 1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01,
+          1.e+02, 1.e+03, 1.e+04, 1.e+05, 1.e+06]),
+            cv=None, fit_intercept=True, gcv_mode=None, normalize=False,
+            scoring=None, store_cv_values=False)
+    >>> reg.alpha_
+    0.01
+
+Specifying the value of the `cv` attribute will trigger the use of
+cross-validation with `GridSearchCV`, for example `cv=10` for 10-fold
+cross-validation, rather than Generalized Cross-Validation.
 
 .. topic:: References
 

diff --git a/doc/whats_new/v0.21.rst b/doc/whats_new/v0.21.rst
@@ -38,6 +38,8 @@ random sampling procedures.
   seed, including :class:`linear_model.LogisticRegression`,
   :class:`linear_model.LogisticRegressionCV`, :class:`linear_model.Ridge`,
   and :class:`linear_model.RidgeCV` with 'sag' solver. |Fix|
+- :class:`linear_model.ridge.RidgeCV` when using generalized cross-validation
+  with sparse inputs. |Fix|
 
 
 Details are listed in the changelog below.
@@ -384,7 +386,7 @@ Support for Python 3.4 and below has been officially dropped.
 :mod:`sklearn.linear_model`
 ...........................
 
-- |Enhancement| :mod:`linear_model.ridge` now preserves ``float32`` and
+- |Enhancement| :class:`linear_model.Ridge` now preserves ``float32`` and
   ``float64`` dtypes. :issues:`8769` and :issues:`11000` by
   :user:`Guillaume Lemaitre <glemaitre>`, and :user:`Joan Massich <massich>`
 
@@ -482,6 +484,10 @@ Support for Python 3.4 and below has been officially dropped.
   in version 0.21 and will be removed in version 0.23.
   :pr:`12821` by :user:`Nicolas Hug <NicolasHug>`.
 
+- |Fix| :class:`linear_model.ridge.RidgeCV` with generalized cross-validation
+  now correctly fits an intercept when ``fit_intercept=True`` and the design
+  matrix is sparse. :issue:`13350` by :user:`Jérôme Dockès <jeromedockes>`
+
 :mod:`sklearn.manifold`
 .......................