scikit-learn · shaz13 · May 25, 2018 · May 25, 2018 · May 26, 2018 · May 27, 2018
diff --git a/doc/whats_new/v0.20.rst b/doc/whats_new/v0.20.rst
@@ -216,6 +216,11 @@ Preprocessing
 
 Model evaluation and meta-estimators
 
+- The default of ``n_splits`` parameter of :class:`model_selection.KFold` is
+  deprecated in version 0.20 and will be changed from ``n_splits=3`` to
+  ``n_splits=5`` in version 0.22.
+  :issue:`11129` by :user:`Mohammad Shahebaz <shaz13>`
+
 - A scorer based on :func:`metrics.brier_score_loss` is also available.
   :issue:`9521` by :user:`Hanmin Qin <qinhanmin2014>`.
 

diff --git a/sklearn/linear_model/tests/test_least_angle.py b/sklearn/linear_model/tests/test_least_angle.py
@@ -424,6 +424,7 @@ def test_lars_cv():
 
 def test_lars_cv_max_iter():
     with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter(action='ignore', category=FutureWarning)
         X = diabetes.data
         y = diabetes.target
         rng = np.random.RandomState(42)

diff --git a/sklearn/model_selection/_split.py b/sklearn/model_selection/_split.py
@@ -367,6 +367,10 @@ class KFold(_BaseKFold):
         If None, the random number generator is the RandomState instance used
         by `np.random`. Used when ``shuffle`` == True.
 
+    .. versionchanged:: 0.20
+        The default value ``n_splits=3`` is deprecated in version 0.20 and will
+        be changed to ``n_splits=5``in version 0.22.
+
     Examples
     --------
     >>> from sklearn.model_selection import KFold
@@ -1859,7 +1863,7 @@ def split(self, X=None, y=None, groups=None):
             yield train, test
 
 
-def check_cv(cv=3, y=None, classifier=False):
+def check_cv(cv=None, y=None, classifier=False):
     """Input checker utility for building a cross-validator
 
     Parameters
@@ -1894,6 +1898,9 @@ def check_cv(cv=3, y=None, classifier=False):
         splits via the ``split`` method.
     """
     if cv is None:
+        warnings.warn("The default value of n_splits=3 is deprecated"
+                      " in version 0.20 and will be changed to "
+                      "n_splits=5 in version 0.22", FutureWarning)
         cv = 3
 
     if isinstance(cv, numbers.Integral):
@@ -2058,6 +2065,7 @@ def train_test_split(*arrays, **options):
 # Tell nose that train_test_split is not a test
 train_test_split.__test__ = False
 
+
 def _build_repr(self):
     # XXX This is copied from BaseEstimator's get_params
     cls = self.__class__

diff --git a/sklearn/model_selection/tests/test_search.py b/sklearn/model_selection/tests/test_search.py
@@ -138,6 +138,7 @@ def test_validate_parameter_grid_input(input, error_type, error_message):
     with pytest.raises(error_type, message=error_message):
         ParameterGrid(input)
 
+
 def test_parameter_grid():
 
     # Test basic properties of ParameterGrid.
@@ -359,14 +360,17 @@ def test_return_train_score_warn():
     estimators = [GridSearchCV(LinearSVC(random_state=0), grid, iid=False),
                   RandomizedSearchCV(LinearSVC(random_state=0), grid,
                                      n_iter=2, iid=False)]
-
+    msg_nsplit = ("The default value of n_splits=3 is deprecated in "
+                  "version 0.20 and will be changed to n_splits=5 "
+                  "in version 0.22")
     result = {}
     for estimator in estimators:
         for val in [True, False, 'warn']:
             estimator.set_params(return_train_score=val)
             fit_func = ignore_warnings(estimator.fit,
                                        category=ConvergenceWarning)
-            result[val] = assert_no_warnings(fit_func, X, y).cv_results_
+            result[val] = assert_warns_message(FutureWarning, msg_nsplit,
+                                               fit_func, X, y).cv_results_
 
     train_keys = ['split0_train_score', 'split1_train_score',
                   'split2_train_score', 'mean_train_score', 'std_train_score']
@@ -1567,7 +1571,6 @@ def test_deprecated_grid_search_iid():
     grid = GridSearchCV(SVC(gamma='scale'), param_grid={'C': [1]}, cv=3)
     # no warning with equally sized test sets
     assert_no_warnings(grid.fit, X, y)
-
     grid = GridSearchCV(SVC(gamma='scale'), param_grid={'C': [1]}, cv=5)
     # warning because 54 % 5 != 0
     assert_warns_message(DeprecationWarning, depr_message, grid.fit, X, y)

diff --git a/sklearn/model_selection/tests/test_validation.py b/sklearn/model_selection/tests/test_validation.py
@@ -396,12 +396,14 @@ def test_cross_validate_return_train_score_warn():
 
     X, y = make_classification(random_state=0)
     estimator = MockClassifier()
-
+    msg_nsplit = ("The default value of n_splits=3 is deprecated in "
+                  "version 0.20 and will be changed to n_splits=5 "
+                  "in version 0.22")
     result = {}
     for val in [False, True, 'warn']:
-        result[val] = assert_no_warnings(cross_validate, estimator, X, y,
-                                         return_train_score=val)
-
+        result[val] = assert_warns_message(FutureWarning, msg_nsplit,
+                                           cross_validate, estimator, X, y,
+                                           return_train_score=val)
     msg = (
         'You are accessing a training score ({!r}), '
         'which will not be available by default '
@@ -1194,7 +1196,8 @@ def test_validation_curve():
             MockEstimatorWithParameter(), X, y, param_name="param",
             param_range=param_range, cv=2
         )
-    if len(w) > 0:
+    # Expected single FutureWarning for deprecation of n_splits=3
+    if len(w) != 0:
         raise RuntimeError("Unexpected warning: %r" % w[0].message)
 
     assert_array_almost_equal(train_scores.mean(axis=1), param_range)