svn commit: r908248 - in /websites/staging/mahout/trunk/content: ./ users/basics/quickstart.html

[bu...@apache.org]

Author: buildbot
Date: Tue May  6 21:04:29 2014
New Revision: 908248

Log:
Staging update by buildbot for mahout

Modified:
    websites/staging/mahout/trunk/content/   (props changed)
    websites/staging/mahout/trunk/content/users/basics/quickstart.html

Propchange: websites/staging/mahout/trunk/content/
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--- cms:source-revision (original)
+++ cms:source-revision Tue May  6 21:04:29 2014
@@ -1 +1 @@
-1592444
+1592883

Modified: websites/staging/mahout/trunk/content/users/basics/quickstart.html
==============================================================================
--- websites/staging/mahout/trunk/content/users/basics/quickstart.html (original)
+++ websites/staging/mahout/trunk/content/users/basics/quickstart.html Tue May  6 21:04:29 2014
@@ -258,9 +258,9 @@ If you would like to import the latest r
 <h4 id="clustering">Clustering</h4>
 <p>Check the <a href="/users/clustering/clustering-of-synthetic-control-data.html">Synthetic data</a> example.</p>
 <h4 id="classification">Classification</h4>
-<p>If you are interested in how to train a <strong>Naive Bayes</strong> model, look at the <a href="/users/clustering/twenty-newsgroups.html">20 newsgroups</a> example or the <a href="/users/classification/wikipedia-bayes-example.html">naive bayes wikipedia example</a> example.</p>
-<p>If you plan to build a <strong>Hidden Markov Model</strong> for speech recognition, the example <a href="/users/stuff/hidden-markov-models.html">here</a> might be instructive. </p>
-<p>Or you could build a <strong>Random Forest</strong> model by following this <a href="/users/stuff/partial-implementation.html">quick start page</a>.</p>
+<p>If you are interested in how to train a <strong>Naive Bayes</strong> model, look at the <a href="/users/clustering/twenty-newsgroups.html">20 newsgroups</a> example.</p>
+<p>If you plan to build a <strong>Hidden Markov Model</strong> for speech recognition, the example <a href="/users/classification/hidden-markov-models.html">here</a> might be instructive. </p>
+<p>Or you could build a <strong>Random Forest</strong> model by following this <a href="/users/classification/partial-implementation.html">quick start page</a>.</p>
 <h4 id="working-with-text">Working with Text</h4>
 <p>If you need to convert raw text into word vectors as input to clustering or classification algorithms, please refer to this page on <a href="/users/basics/creating-vectors-from-text.html">how to create vectors from text</a>.</p>
    </div>