From 9ce43dd2a802a55a6091a21220aed2c7b9493f63 Mon Sep 17 00:00:00 2001
From: Juan Martin Loyola <jmloyola@outlook.com>
Date: Wed, 8 Sep 2021 16:47:39 -0300
Subject: [PATCH 1/2] Remove SelectFwe from DOCSTRING_IGNORE_LIST

---
 maint_tools/test_docstrings.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/maint_tools/test_docstrings.py b/maint_tools/test_docstrings.py
index 612817e23f6b9..2d18b8d7fa6ea 100644
--- a/maint_tools/test_docstrings.py
+++ b/maint_tools/test_docstrings.py
@@ -65,7 +65,6 @@
     "SelectFdr",
     "SelectFpr",
     "SelectFromModel",
-    "SelectFwe",
     "SelectKBest",
     "SelfTrainingClassifier",
     "SequentialFeatureSelector",

From ce04847a6f08d8e880dc2f231cb0d1dfb4f3893f Mon Sep 17 00:00:00 2001
From: Juan Martin Loyola <jmloyola@outlook.com>
Date: Wed, 8 Sep 2021 16:48:05 -0300
Subject: [PATCH 2/2] Fix numpydocs from SelectFwe

---
 .../_univariate_selection.py                  | 24 +++++++++----------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/sklearn/feature_selection/_univariate_selection.py b/sklearn/feature_selection/_univariate_selection.py
index 95b244bd2cca6..159e25542ef37 100644
--- a/sklearn/feature_selection/_univariate_selection.py
+++ b/sklearn/feature_selection/_univariate_selection.py
@@ -785,7 +785,7 @@ def _get_support_mask(self):
 
 
 class SelectFwe(_BaseFilter):
-    """Filter: Select the p-values corresponding to Family-wise error rate
+    """Filter: Select the p-values corresponding to Family-wise error rate.
 
     Read more in the :ref:`User Guide <univariate_feature_selection>`.
 
@@ -800,17 +800,6 @@ class SelectFwe(_BaseFilter):
     alpha : float, default=5e-2
         The highest uncorrected p-value for features to keep.
 
-    Examples
-    --------
-    >>> from sklearn.datasets import load_breast_cancer
-    >>> from sklearn.feature_selection import SelectFwe, chi2
-    >>> X, y = load_breast_cancer(return_X_y=True)
-    >>> X.shape
-    (569, 30)
-    >>> X_new = SelectFwe(chi2, alpha=0.01).fit_transform(X, y)
-    >>> X_new.shape
-    (569, 15)
-
     Attributes
     ----------
     scores_ : array-like of shape (n_features,)
@@ -842,6 +831,17 @@ class SelectFwe(_BaseFilter):
     SelectFdr : Select features based on an estimated false discovery rate.
     GenericUnivariateSelect : Univariate feature selector with configurable
         mode.
+
+    Examples
+    --------
+    >>> from sklearn.datasets import load_breast_cancer
+    >>> from sklearn.feature_selection import SelectFwe, chi2
+    >>> X, y = load_breast_cancer(return_X_y=True)
+    >>> X.shape
+    (569, 30)
+    >>> X_new = SelectFwe(chi2, alpha=0.01).fit_transform(X, y)
+    >>> X_new.shape
+    (569, 15)
     """
 
     def __init__(self, score_func=f_classif, *, alpha=5e-2):