From 200b28c89f37a6e6eb13ac47b72ce01f77756430 Mon Sep 17 00:00:00 2001
From: Gabriel <Gabriel-p@users.noreply.github.com>
Date: Fri, 16 Oct 2015 18:24:33 -0300
Subject: [PATCH]  fix typo

---
 dev/modules/clustering.html | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/dev/modules/clustering.html b/dev/modules/clustering.html
index c505794becde4..770ec6d2ef2c5 100644
--- a/dev/modules/clustering.html
+++ b/dev/modules/clustering.html
@@ -387,7 +387,7 @@ <h2>2.3.1. Overview of clustering methods<a class="headerlink" href="#overview-o
 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 <tt class="docutils literal"><span class="pre">init='kmeans++'</span></tt> 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.</p>
 <p>A parameter can be given to allow K-means to be run in parallel, called
 <tt class="docutils literal"><span class="pre">n_jobs</span></tt>. Giving this parameter a positive value uses that many processors
@@ -1485,4 +1485,4 @@ <h4>2.3.9.4.2. Drawbacks<a class="headerlink" href="#id19" title="Permalink to t
             customSearchControl.draw('cse', options); }, true);
     </script>
   </body>
-</html>
\ No newline at end of file
+</html>