svn commit: r887499 - in /websites/staging/mahout/trunk/content: ./ users/clustering/mean-shift-clustering.html

[bu...@apache.org]

Author: buildbot
Date: Thu Nov 21 11:18:24 2013
New Revision: 887499

Log:
Staging update by buildbot for mahout

Modified:
    websites/staging/mahout/trunk/content/   (props changed)
    websites/staging/mahout/trunk/content/users/clustering/mean-shift-clustering.html

Propchange: websites/staging/mahout/trunk/content/
------------------------------------------------------------------------------
--- cms:source-revision (original)
+++ cms:source-revision Thu Nov 21 11:18:24 2013
@@ -1 +1 @@
-1544119
+1544121

Modified: websites/staging/mahout/trunk/content/users/clustering/mean-shift-clustering.html
==============================================================================
--- websites/staging/mahout/trunk/content/users/clustering/mean-shift-clustering.html (original)
+++ websites/staging/mahout/trunk/content/users/clustering/mean-shift-clustering.html Thu Nov 21 11:18:24 2013
@@ -509,19 +509,19 @@ deviation. See the README file in the <a
 </ul>
 <p>In the first image, the points are plotted and the 3-sigma boundaries of
 their generator are superimposed. </p>
-<p><img alt="clustering" src="../../SampleData.png" /></p>
+<p><img alt="clustering" src="../../images/SampleData.png" /></p>
 <p>In the second image, the resulting clusters (k=3) are shown superimposed
 upon the sample data. In this image, each cluster renders in a different
 color and the T1 and T2 radii are superimposed upon the final cluster
 centers determined by the algorithm. Mean Shift does an excellent job of
 clustering this data, though by its design the cluster membership is unique
 and the clusters do not overlap. </p>
-<p><img alt="clustering" src="../../MeanShift.png" /></p>
+<p><img alt="clustering" src="../../images/MeanShift.png" /></p>
 <p>The third image shows the results of running Mean Shift on a different data
 set (see <a href="dirichlet-process-clustering.html">Dirichlet Process Clustering</a>
  for details) which is generated using asymmetrical standard deviations.
 Mean Shift does an excellent job of clustering this data set too.</p>
-<p><img alt="clustering" src="../../2dMeanShift.png" /></p>
+<p><img alt="clustering" src="../../images/2dMeanShift.png" /></p>
    </div>
   </div>     
 </div>