DOC: mark weights as optional

Author: tacaswell

sklearn/neighbors/classification.py

@@ -29,7 +29,7 @@ class KNeighborsClassifier(NeighborsBase, KNeighborsMixin,
     n_neighbors : int, optional (default = 5)
         Number of neighbors to use by default for :meth:`k_neighbors` queries.
 
-    weights : str or callable
+    weights : str or callable, optional (default = 'uniform')
         weight function used in prediction.  Possible values:
 
         - 'uniform' : uniform weights.  All points in each neighborhood
@@ -41,8 +41,6 @@ class KNeighborsClassifier(NeighborsBase, KNeighborsMixin,
           array of distances, and returns an array of the same shape
           containing the weights.
 
-        Uniform weights are used by default.
-
     algorithm : {'auto', 'ball_tree', 'kd_tree', 'brute'}, optional
         Algorithm used to compute the nearest neighbors: