updated docs

docs/docs/ml.xml

@@ -111,6 +111,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
          <item>pick_initial_centers</item> 
          <item>kkmeans</item>
          <item>find_clusters_using_kmeans</item> 
+         <item>find_clusters_using_angular_kmeans</item> 
          <item>nearest_center</item> 
          <item>newman_cluster</item> 
          <item>spectral_cluster</item> 
@@ -357,7 +358,23 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
          <file>dlib/clustering.h</file>
          <spec_file link="true">dlib/svm/kkmeans_abstract.h</spec_file>
          <description>
-            This is just a simple linear kmeans clustering implementation.
+            This is a simple linear kmeans clustering implementation.
+            It uses Euclidean distance to compare samples.
+         </description>
+                                 
+      </component>
+
+   <!-- ************************************************************************* -->
+
+      <component>
+         <name>find_clusters_using_angular_kmeans</name>
+         <file>dlib/clustering.h</file>
+         <spec_file link="true">dlib/svm/kkmeans_abstract.h</spec_file>
+         <description>
+            This is a simple linear kmeans clustering implementation.
+            To compare a sample to a cluster, it measures the angle between them
+            with respect to the origin.  Therefore, it tries to find clusters
+            of points that all have small angles between each cluster member.
          </description>
                                  
       </component>

docs/docs/term_index.xml

@@ -424,6 +424,7 @@
          <term file="dlib/statistics/dpca_abstract.h.html" name="discriminant_pca_error"  include="dlib/statistics.h"/>
          <term file="ml.html" name="kkmeans"                                        include="dlib/clustering.h"/>
          <term file="ml.html" name="find_clusters_using_kmeans"                     include="dlib/clustering.h"/>
+         <term file="ml.html" name="find_clusters_using_angular_kmeans"             include="dlib/clustering.h"/>
          <term file="ml.html" name="nearest_center"                                 include="dlib/clustering.h"/>
          <term file="ml.html" name="newman_cluster"                                 include="dlib/clustering.h"/>
          <term file="ml.html" name="spectral_cluster"                               include="dlib/clustering.h"/>