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aksnzhy committed Dec 9, 2017
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9 changes: 7 additions & 2 deletions _build/html/_sources/command_line.rst.txt
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Expand Up @@ -93,10 +93,15 @@ Users can choose different machine learning models by using ``-s`` option ::
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. You can give a ``libffm`` file to LR and FM, and
at that time xLearn will treat the data as ``libsvm`` format.
input data should be the ``libffm`` format. You can give a ``libffm`` file to LR and FM. At that
time, xLearn will treat this data as ``libsvm`` format ::

./xlearn_train ./small_train.txt -s 0 # Using linear model
./xlearn_train ./small_train.txt -s 1 # Using factorization machine (FM)
./xlearn_train ./small_train.txt -s 2 # Using field-awre factorization machine (FFM)

Set Validation Dataset
----------------------------------------

.. toctree::
:hidden:
15 changes: 12 additions & 3 deletions _build/html/command_line.html
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Expand Up @@ -94,7 +94,8 @@
<li class="toctree-l1"><a class="reference internal" href="install.html">Installation Guide</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">xLearn Command Line Guide</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#quick-start">Quick Start</a></li>
<li class="toctree-l2"><a class="reference internal" href="#choose-machine-learning-model">Choose Machine Learning Model</a><ul class="simple">
<li class="toctree-l2"><a class="reference internal" href="#choose-machine-learning-model">Choose Machine Learning Model</a></li>
<li class="toctree-l2"><a class="reference internal" href="#set-validation-dataset">Set Validation Dataset</a><ul class="simple">
</ul>
</li>
</ul>
Expand Down Expand Up @@ -256,8 +257,16 @@ <h2>Choose Machine Learning Model<a class="headerlink" href="#choose-machine-lea
</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. 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>
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. At that
time, xLearn will treat this data as <code class="docutils literal"><span class="pre">libsvm</span></code> format</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="o">./</span><span class="n">xlearn_train</span> <span class="o">./</span><span class="n">small_train</span><span class="o">.</span><span class="n">txt</span> <span class="o">-</span><span class="n">s</span> <span class="mi">0</span> <span class="c1"># Using linear model</span>
<span class="o">./</span><span class="n">xlearn_train</span> <span class="o">./</span><span class="n">small_train</span><span class="o">.</span><span class="n">txt</span> <span class="o">-</span><span class="n">s</span> <span class="mi">1</span> <span class="c1"># Using factorization machine (FM)</span>
<span class="o">./</span><span class="n">xlearn_train</span> <span class="o">./</span><span class="n">small_train</span><span class="o">.</span><span class="n">txt</span> <span class="o">-</span><span class="n">s</span> <span class="mi">2</span> <span class="c1"># Using field-awre factorization machine (FFM)</span>
</pre></div>
</div>
</div>
<div class="section" id="set-validation-dataset">
<h2>Set Validation Dataset<a class="headerlink" href="#set-validation-dataset" title="Permalink to this headline"></a></h2>
<blockquote>
<div><div class="toctree-wrapper compound">
</div>
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9 changes: 7 additions & 2 deletions command_line.rst
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Expand Up @@ -93,10 +93,15 @@ Users can choose different machine learning models by using ``-s`` option ::
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. You can give a ``libffm`` file to LR and FM, and
at that time xLearn will treat the data as ``libsvm`` format.
input data should be the ``libffm`` format. You can give a ``libffm`` file to LR and FM. At that
time, xLearn will treat this data as ``libsvm`` format ::

./xlearn_train ./small_train.txt -s 0 # Using linear model
./xlearn_train ./small_train.txt -s 1 # Using factorization machine (FM)
./xlearn_train ./small_train.txt -s 2 # Using field-awre factorization machine (FFM)

Set Validation Dataset
----------------------------------------

.. toctree::
:hidden:

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