updated the docs

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%402248

docs/docs/algorithms.xml

@@ -56,6 +56,7 @@
                <item>decision_function</item>
                <item>probabilistic_decision_function</item>
                <item>krls</item>
+               <item>one_class</item>
             </sub>
          </item>
       </section>
@@ -678,6 +679,28 @@
       </component>
       
       
+   <!-- ************************************************************************* -->
+      
+      <component>
+         <name>one_class</name>
+         <file>dlib/svm.h</file>
+         <spec_file link="true">dlib/svm/one_class_abstract.h</spec_file>
+         <description>
+                This is an implementation of an online algorithm for recursively estimating the
+                center of mass of a sequence of training points.  It uses the sparsification technique
+                described in the paper The Kernel Recursive Least Squares Algorithm by Yaakov Engel.
+
+            <p>
+                This object then allows you to compute the distance between the center of mass
+                and any test points.  So you can use this object to predict how similar a test
+                point is to the data this object has been trained on (larger distances from the
+                centroid indicate dissimilarity/anomalous points).
+            </p>
+         </description>
+                                 
+      </component>
+      
+      
    <!-- ************************************************************************* -->
       
       <component>

docs/docs/index.xml

@@ -115,7 +115,8 @@
                <ul>
                   <li><a href="algorithms.html#mlp">multi layer perceptrons</a> </li>  
                   <li><a href="algorithms.html#svm_nu_train">nu support vector machines</a> for classification</li>
-                  <li><a href="algorithms.html#krls">kernel RLS regression</a></li>
+                  <li>An online <a href="algorithms.html#krls">kernel RLS regression</a> algorithm</li>
+                  <li>An online <a href="algorithms.html#one_class">one class classifier</a></li>
                   <li>Bayesian Network inference algorithms such as the 
                      <a href="algorithms.html#bayesian_network_join_tree">join tree</a> algorithm and 
                      <a href="algorithms.html#bayesian_network_gibbs_sampler">Gibbs sampler</a> Markov Chain Monte Carlo algorithm</li>

docs/docs/term_index.xml

@@ -375,6 +375,7 @@
          <term link="algorithms.html#vector" name="vector"/>
          <term link="algorithms.html#point" name="point"/>
          <term link="algorithms.html#krls" name="krls"/>
+         <term link="algorithms.html#one_class" name="one_class"/>
          
          <term link="dlib/svm/svm_abstract.h.html#maximum_nu" name="maximum_nu"/>