DOC Fixed typo in clustering.rst
@@ -202,7 +202,7 @@ As a result, the computation is often done several times, with different
initializations of the centroids. One method to help address this issue is the
k-means++ initialization scheme, which has been implemented in scikit-learn
(use the ``init='k-means++'`` parameter). This initializes the centroids to be
-(generally) distant from each other, leading to provably better results than
+(generally) distant from each other, leading to probably better results than
random initialization, as shown in the reference.
K-means++ can also be called independently to select seeds for other
