COSMIT pep8

Author: amueller

sklearn/linear_model/isotonic_regression_.py

@@ -43,7 +43,7 @@ def isotonic_regression(y, weight=None, y_min=None, y_max=None):
 
     References
     ----------
-    "Active set algorithms for isotonic regression; A unifying framework" 
+    "Active set algorithms for isotonic regression; A unifying framework"
     by Michael J. Best and Nilotpal Chakravarti, section 3.
     """
     if weight is None:

sklearn/mixture/gmm.py

@@ -10,10 +10,9 @@
 #         Bertrand Thirion <[email protected]>
 
 import numpy as np
-import warnings
 
 from ..base import BaseEstimator
-from ..utils import check_random_state, deprecated
+from ..utils import check_random_state
 from ..utils.extmath import logsumexp, pinvh
 from .. import cluster
 

sklearn/neighbors/unsupervised.py

@@ -60,7 +60,8 @@ class NearestNeighbors(NeighborsBase, KNeighborsMixin,
       >>> neigh.fit(samples)  #doctest: +ELLIPSIS
       NearestNeighbors(...)
 
-      >>> neigh.kneighbors([[0, 0, 1.3]], 2, return_distance=False) #doctest: +ELLIPSIS
+      >>> neigh.kneighbors([[0, 0, 1.3]], 2, return_distance=False)
+      ... #doctest: +ELLIPSIS
       array([[2, 0]]...)
 
       >>> neigh.radius_neighbors([0, 0, 1.3], 0.4, return_distance=False)