updated docs

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403545

docs/docs/ml.xml

@@ -121,6 +121,13 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
          <item>normalized_function</item>
       </section>
 
+      <section>
+         <name>Data IO</name>
+         <item>load_libsvm_formatted_data</item> 
+         <item>save_libsvm_formatted_data</item> 
+         <item>sparse_to_dense</item>
+      </section>
+
       <section>
          <name>Miscellaneous</name>
          <item>vector_normalizer</item> 
@@ -905,6 +912,49 @@ Davis E. King. <a href="http://www.jmlr.org/papers/volume10/king09a/king09a.pdf"
                                  
       </component>
       
+   <!-- ************************************************************************* -->
+      
+      <component>
+         <name>load_libsvm_formatted_data</name>
+         <file>dlib/data_io.h</file>
+         <spec_file link="true">dlib/data_io/libsvm_io_abstract.h</spec_file>
+         <description>
+            This is a function that loads the data from a file that uses
+            the LIBSVM format.  It loads the data into a std::vector of
+            <a href="dlib/svm/sparse_vector_abstract.h.html#sparse_vectors">sparse vectors</a>.
+            If you want to load data into dense vectors (i.e.
+            dlib::matrix objects) then you can use the <a href="#sparse_to_dense">sparse_to_dense</a>
+            function to perform the conversion.
+         </description>
+                                 
+      </component>
+      
+   <!-- ************************************************************************* -->
+      
+      <component>
+         <name>save_libsvm_formatted_data</name>
+         <file>dlib/data_io.h</file>
+         <spec_file link="true">dlib/data_io/libsvm_io_abstract.h</spec_file>
+         <description>
+            This is actually a pair of overloaded functions.  Between the two of them
+            they let you save <a href="dlib/svm/sparse_vector_abstract.h.html#sparse_vectors">sparse</a> 
+            or dense data vectors to file using the LIBSVM format.  
+         </description>
+      </component>
+      
+   <!-- ************************************************************************* -->
+      
+      <component>
+         <name>sparse_to_dense</name>
+         <file>dlib/data_io.h</file>
+         <spec_file link="true">dlib/data_io/libsvm_io_abstract.h</spec_file>
+         <description>
+            This is a simple function that takes a std::vector of 
+            <a href="dlib/svm/sparse_vector_abstract.h.html#sparse_vectors">sparse vectors</a> 
+            and returns to you the equivalent std::vector of dense vectors. 
+         </description>
+      </component>
+      
    <!-- ************************************************************************* -->
       
       <component>

docs/docs/release_notes.xml

@@ -22,6 +22,7 @@ New Stuff:
    - Added the running_covariance object 
    - Added a simple linear (i.e. non-kernelized) kmeans implementation
    - Added support for serializing dlib::int64
+   - Added some functions to load and save LIBSVM formatted data files.
 
 Non-Backwards Compatible Changes:
    - Changed the definition of dlib's sparse vector format to require

docs/docs/term_index.xml

@@ -114,6 +114,9 @@
 
          <term file="dlib/svm/pegasos_abstract.h.html" name="replicate_settings"/>
          <term file="ml.html" name="mlp"/>
+         <term file="ml.html" name="load_libsvm_formatted_data"/>
+         <term file="ml.html" name="save_libsvm_formatted_data"/>
+         <term file="ml.html" name="sparse_to_dense"/>
          <term link="ml.html#mlp" name="multi-layer perceptron"/>
          <term link="ml.html#mlp" name="neural network"/>
          <term file="ml.html" name="svm_pegasos"/>