deprecation warnings, indent fix

Author: jaquesgrobler

doc/modules/neighbors.rst

@@ -54,9 +54,9 @@ of each option, see `Nearest Neighbor Algorithms`_.
     .. warning::
 
         Regarding the Nearest Neighbors algorithms, if it is found that two
-	neighbors, neighbor `k+1` and `k`, have identical distances but
-	but different labels, the results will depend on the odering of the
-	training data.
+        neighbors, neighbor `k+1` and `k`, have identical distances but
+        but different labels, the results will depend on the odering of the
+        training data.
 
 .. _classification:
 

sklearn/neighbors/classification.py

@@ -7,6 +7,8 @@
 #
 # License: BSD, (C) INRIA, University of Amsterdam
 
+import warnings
+
 import numpy as np
 from scipy import stats
 from ..utils.extmath import weighted_mode
@@ -103,7 +105,13 @@ class KNeighborsClassifier(NeighborsBase, KNeighborsMixin,
 
     def __init__(self, n_neighbors=5,
                  weights='uniform',
-                 algorithm='auto', leaf_size=30, p=2):
+                 algorithm='auto', leaf_size=30, p=2, **kwargs):
+        if kwargs:
+            if 'warn_on_equidistant' in kwargs:
+                warnings.warn("The warn_on_equidistant parameter is "
+                              "deprecated and will be removed in the future.",
+                              DeprecationWarning,
+                              stacklevel=2)
         self._init_params(n_neighbors=n_neighbors,
                           algorithm=algorithm,
                           leaf_size=leaf_size, p=p)

sklearn/neighbors/regression.py

@@ -7,6 +7,8 @@
 #
 # License: BSD, (C) INRIA, University of Amsterdam
 
+import warnings
+
 import numpy as np
 
 from .base import \
@@ -102,7 +104,13 @@ class KNeighborsRegressor(NeighborsBase, KNeighborsMixin,
     """
 
     def __init__(self, n_neighbors=5, weights='uniform',
-                 algorithm='auto', leaf_size=30, p=2):
+                 algorithm='auto', leaf_size=30, p=2, **kwargs):
+        if kwargs:
+            if 'warn_on_equidistant' in kwargs:
+                warnings.warn("The warn_on_equidistant parameter is "
+                              "deprecated and will be removed in the future",
+                              DeprecationWarning,
+                              stacklevel=2)
         self._init_params(n_neighbors=n_neighbors,
                           algorithm=algorithm,
                           leaf_size=leaf_size, p=p)