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Posted to commits@mahout.apache.org by bu...@apache.org on 2013/11/21 12:27:34 UTC
svn commit: r887506 - in /websites/staging/mahout/trunk/content: ./
users/clustering/llr---log-likelihood-ratio.html
Author: buildbot
Date: Thu Nov 21 11:27:34 2013
New Revision: 887506
Log:
Staging update by buildbot for mahout
Modified:
websites/staging/mahout/trunk/content/ (props changed)
websites/staging/mahout/trunk/content/users/clustering/llr---log-likelihood-ratio.html
Propchange: websites/staging/mahout/trunk/content/
------------------------------------------------------------------------------
--- cms:source-revision (original)
+++ cms:source-revision Thu Nov 21 11:27:34 2013
@@ -1 +1 @@
-1544125
+1544126
Modified: websites/staging/mahout/trunk/content/users/clustering/llr---log-likelihood-ratio.html
==============================================================================
--- websites/staging/mahout/trunk/content/users/clustering/llr---log-likelihood-ratio.html (original)
+++ websites/staging/mahout/trunk/content/users/clustering/llr---log-likelihood-ratio.html Thu Nov 21 11:27:34 2013
@@ -381,8 +381,9 @@
<div id="content-wrap" class="clearfix">
<div id="main">
- <p>{excerpt}Likelihood ratio test is used to compare the fit of two models one
-of which is nested within the other.{excerpt}</p>
+ <h1 id="likelihood-ratio-test">Likelihood ratio test</h1>
+<p><em>Likelihood ratio test is used to compare the fit of two models one
+of which is nested within the other.</em></p>
<p>In the context of machine learning and the Mahout project in particular,
the term LLR is usually meant to refer to a test of significance for two
binomial distributions, also known as the G squared statistic. This is a
@@ -408,10 +409,12 @@ and since the ordering imposed by the LL
fluctuation, this technique can provide very strong results in very sparse
problems where the potential number of features vastly out-numbers the
number of training examples and where features are highly interdependent.</p>
-<p>See Also:
- * http://tdunning.blogspot.com/2008/03/surprise-and-coincidence.html
- * http://en.wikipedia.org/wiki/G-test
- * http://en.wikipedia.org/wiki/Likelihood-ratio_test</p>
+<p>See Also: </p>
+<ul>
+<li><a href="http://tdunning.blogspot.com/2008/03/surprise-and-coincidence.html">Blog post "surprise and coincidence"</a></li>
+<li><a href="http://en.wikipedia.org/wiki/G-test">G-Test</a></li>
+<li><a href="http://en.wikipedia.org/wiki/Likelihood-ratio_test">Likelihood Ratio Test</a></li>
+</ul>
</div>
</div>
</div>