diff --git a/sklearn/datasets/kddcup99.py b/sklearn/datasets/kddcup99.py
index 89c74238bc4f304ac0f813f711487ad75cda17ab..6d52c5b6214b241efb86b62425f5e4faf14299de 100644
--- a/sklearn/datasets/kddcup99.py
+++ b/sklearn/datasets/kddcup99.py
@@ -222,7 +222,7 @@ def fetch_kddcup99(subset=None, data_home=None, shuffle=False,
     return Bunch(data=data, target=target)
 
 
-def _fetch_brute_kddcup99(subset=None, data_home=None,
+def _fetch_brute_kddcup99(data_home=None,
                           download_if_missing=True, random_state=None,
                           shuffle=False, percent10=True):
 
@@ -230,10 +230,6 @@ def _fetch_brute_kddcup99(subset=None, data_home=None,
 
     Parameters
     ----------
-    subset : None, 'SA', 'SF', 'http', 'smtp'
-        To return the corresponding classical subsets of kddcup 99.
-        If None, return the entire kddcup 99 dataset.
-
     data_home : string, optional
         Specify another download and cache folder for the datasets. By default
         all scikit-learn data is stored in '~/scikit_learn_data' subfolders.
diff --git a/sklearn/model_selection/_split.py b/sklearn/model_selection/_split.py
index 3f228e85c43e849782dd93fc6cf6090688e4c3ed..4bcc0ae1c534900f1c05d70f2de562e0ef6bf18f 100644
--- a/sklearn/model_selection/_split.py
+++ b/sklearn/model_selection/_split.py
@@ -566,7 +566,7 @@ class StratifiedKFold(_BaseKFold):
     def __init__(self, n_splits=3, shuffle=False, random_state=None):
         super(StratifiedKFold, self).__init__(n_splits, shuffle, random_state)
 
-    def _make_test_folds(self, X, y=None, groups=None):
+    def _make_test_folds(self, X, y=None):
         if self.shuffle:
             rng = check_random_state(self.random_state)
         else:
diff --git a/sklearn/neural_network/multilayer_perceptron.py b/sklearn/neural_network/multilayer_perceptron.py
index ec1196a3e2ac6225556dd2f11b7a86e6e1dd6478..d4adfd9107f6e6592ac18e8f01373287fa128dd9 100644
--- a/sklearn/neural_network/multilayer_perceptron.py
+++ b/sklearn/neural_network/multilayer_perceptron.py
@@ -640,7 +640,7 @@ class BaseMultilayerPerceptron(six.with_metaclass(ABCMeta, BaseEstimator)):
                                  % self.solver)
         return self._partial_fit
 
-    def _partial_fit(self, X, y, classes=None):
+    def _partial_fit(self, X, y):
         return self._fit(X, y, incremental=True)
 
     def _predict(self, X):