update doc

aksnzhy · Dec 9, 2017 · a4dc35b · a4dc35b
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Showing 6 changed files with 10 additions and 7 deletions.
diff --git a/_build/doctrees/command_line.doctree b/_build/doctrees/command_line.doctree
diff --git a/_build/doctrees/environment.pickle b/_build/doctrees/environment.pickle
diff --git a/_build/html/_sources/command_line.rst.txt b/_build/html/_sources/command_line.rst.txt
@@ -92,8 +92,9 @@ Users can choose different machine learning models by using ``-s`` option ::
          4 -- factorization machines (FM)
          5 -- field-aware factorization machines (FFM)
 
-For LR and FM, the input data can be ``CSV`` or ``libsvm`` data format, while for FFM, the input
-data should be the ``libffm`` format.
+For LR and FM, the input data can be ``CSV`` or ``libsvm`` data format, while for FFM, the 
+input data should be the ``libffm`` format. You can give a ``libffm`` file to LR and FM, and 
+at that time xLearn will treat the data as ``libsvm`` format.
 
 
 

diff --git a/_build/html/command_line.html b/_build/html/command_line.html
@@ -255,8 +255,9 @@ <h2>Choose Machine Learning Model<a class="headerlink" href="#choose-machine-lea
        <span class="mi">5</span> <span class="o">--</span> <span class="n">field</span><span class="o">-</span><span class="n">aware</span> <span class="n">factorization</span> <span class="n">machines</span> <span class="p">(</span><span class="n">FFM</span><span class="p">)</span>
 </pre></div>
 </div>
-<p>For LR and FM, the input data can be <code class="docutils literal"><span class="pre">CSV</span></code> or <code class="docutils literal"><span class="pre">libsvm</span></code> data format, while for FFM, the input
-data should be the <code class="docutils literal"><span class="pre">libffm</span></code> format.</p>
+<p>For LR and FM, the input data can be <code class="docutils literal"><span class="pre">CSV</span></code> or <code class="docutils literal"><span class="pre">libsvm</span></code> data format, while for FFM, the
+input data should be the <code class="docutils literal"><span class="pre">libffm</span></code> format. You can give a <code class="docutils literal"><span class="pre">libffm</span></code> file to LR and FM, and
+at that time xLearn will treat the data as <code class="docutils literal"><span class="pre">libsvm</span></code> format.</p>
 <blockquote>
 <div><div class="toctree-wrapper compound">
 </div>

diff --git a/_build/html/searchindex.js b/_build/html/searchindex.js
diff --git a/command_line.rst b/command_line.rst
@@ -92,8 +92,9 @@ Users can choose different machine learning models by using ``-s`` option ::
          4 -- factorization machines (FM)
          5 -- field-aware factorization machines (FFM)
 
-For LR and FM, the input data can be ``CSV`` or ``libsvm`` data format, while for FFM, the input
-data should be the ``libffm`` format.
+For LR and FM, the input data can be ``CSV`` or ``libsvm`` data format, while for FFM, the 
+input data should be the ``libffm`` format. You can give a ``libffm`` file to LR and FM, and 
+at that time xLearn will treat the data as ``libsvm`` format.