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Posted to commits@mahout.apache.org by ap...@apache.org on 2014/06/24 16:46:45 UTC

svn commit: r1605099 - /mahout/site/mahout_cms/trunk/content/users/clustering/k-means-clustering.mdtext

Author: apalumbo
Date: Tue Jun 24 14:46:44 2014
New Revision: 1605099

URL: http://svn.apache.org/r1605099
Log:
MAHOUT-1587: Update website to reflect move to GitHub

Modified:
    mahout/site/mahout_cms/trunk/content/users/clustering/k-means-clustering.mdtext

Modified: mahout/site/mahout_cms/trunk/content/users/clustering/k-means-clustering.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/content/users/clustering/k-means-clustering.mdtext?rev=1605099&r1=1605098&r2=1605099&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/users/clustering/k-means-clustering.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/users/clustering/k-means-clustering.mdtext Tue Jun 24 14:46:44 2014
@@ -30,7 +30,7 @@ remains the same.
 <a name="K-MeansClustering-Quickstart"></a>
 ## Quickstart
 
-[Here](https://svn.apache.org/repos/asf/mahout/trunk/examples/bin/cluster-reuters.sh)
+[Here](https://github.com/apache/mahout/blob/master/examples/bin/cluster-reuters.sh)
  is a short shell script outline that will get you started quickly with
 k-means. This does the following:
 
@@ -148,7 +148,7 @@ DistanceMeasure.
 The following images illustrate k-Means clustering applied to a set of
 randomly-generated 2-d data points. The points are generated using a normal
 distribution centered at a mean location and with a constant standard
-deviation. See the README file in the [/examples/src/main/java/org/apache/mahout/clustering/display/README.txt](http://svn.apache.org/repos/asf/mahout/trunk/examples/src/main/java/org/apache/mahout/clustering/display/README.txt)
+deviation. See the README file in the [/examples/src/main/java/org/apache/mahout/clustering/display/README.txt](https://github.com/apache/mahout/blob/master/examples/src/main/java/org/apache/mahout/clustering/display/README.txt)
  for details on running similar examples.
 
 The points are generated as follows: