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update doc
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@aksnzhy
aksnzhy committed Dec 9, 2017
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6 changes: 5 additions & 1 deletion _build/html/_sources/command_line.rst.txt
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Expand Up @@ -161,14 +161,18 @@ On default, xLearn uses 5-folds cross validation, and users can set the number o
./xlearn_train ./small_train.txt -f 3 --cv

Here, we set the number of folds to ``3``. The xLearn will calcluate the avergae validation loss at the end
of it's message. ::
of it's output message. ::

[------------] Average log_loss: 0.549417
[ ACTION ] Finish Cross-Validation
[ ACTION ] Clear the xLearn environment ...
[------------] Total time cost: 0.03 (sec)


Choose Optimization Method
----------------------------------------





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27 changes: 15 additions & 12 deletions _build/html/command_line.html
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Expand Up @@ -97,6 +97,9 @@
<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></li>
<li class="toctree-l2"><a class="reference internal" href="#cross-validation">Cross Validation</a></li>
<li class="toctree-l2"><a class="reference internal" href="#choose-optimization-method">Choose Optimization Method</a><ul class="simple">
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="python_api.html">xLearn Python API Guide</a></li>
Expand Down Expand Up @@ -323,21 +326,21 @@ <h2>Cross Validation<a class="headerlink" href="#cross-validation" title="Permal
</pre></div>
</div>
<p>Here, we set the number of folds to <code class="docutils literal"><span class="pre">3</span></code>. The xLearn will calcluate the avergae validation loss at the end
of it’s message.</p>
<div class="highlight-default"><div class="highlight"><pre><span></span> <span class="p">[</span><span class="o">------------</span><span class="p">]</span> <span class="n">Average</span> <span class="n">log_loss</span><span class="p">:</span> <span class="mf">0.549417</span>
<span class="p">[</span> <span class="n">ACTION</span> <span class="p">]</span> <span class="n">Finish</span> <span class="n">Cross</span><span class="o">-</span><span class="n">Validation</span>
<span class="p">[</span> <span class="n">ACTION</span> <span class="p">]</span> <span class="n">Clear</span> <span class="n">the</span> <span class="n">xLearn</span> <span class="n">environment</span> <span class="o">...</span>
<span class="p">[</span><span class="o">------------</span><span class="p">]</span> <span class="n">Total</span> <span class="n">time</span> <span class="n">cost</span><span class="p">:</span> <span class="mf">0.03</span> <span class="p">(</span><span class="n">sec</span><span class="p">)</span>





<span class="o">..</span> <span class="n">toctree</span><span class="p">::</span>
<span class="p">:</span><span class="n">hidden</span><span class="p">:</span>
of it’s output message.</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="p">[</span><span class="o">------------</span><span class="p">]</span> <span class="n">Average</span> <span class="n">log_loss</span><span class="p">:</span> <span class="mf">0.549417</span>
<span class="p">[</span> <span class="n">ACTION</span> <span class="p">]</span> <span class="n">Finish</span> <span class="n">Cross</span><span class="o">-</span><span class="n">Validation</span>
<span class="p">[</span> <span class="n">ACTION</span> <span class="p">]</span> <span class="n">Clear</span> <span class="n">the</span> <span class="n">xLearn</span> <span class="n">environment</span> <span class="o">...</span>
<span class="p">[</span><span class="o">------------</span><span class="p">]</span> <span class="n">Total</span> <span class="n">time</span> <span class="n">cost</span><span class="p">:</span> <span class="mf">0.03</span> <span class="p">(</span><span class="n">sec</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="section" id="choose-optimization-method">
<h2>Choose Optimization Method<a class="headerlink" href="#choose-optimization-method" title="Permalink to this headline"></a></h2>
<blockquote>
<div><div class="toctree-wrapper compound">
</div>
</div></blockquote>
</div>
</div>


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2 changes: 1 addition & 1 deletion _build/html/searchindex.js
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6 changes: 5 additions & 1 deletion command_line.rst
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Expand Up @@ -161,14 +161,18 @@ On default, xLearn uses 5-folds cross validation, and users can set the number o
./xlearn_train ./small_train.txt -f 3 --cv

Here, we set the number of folds to ``3``. The xLearn will calcluate the avergae validation loss at the end
of it's message. ::
of it's output message. ::

[------------] Average log_loss: 0.549417
[ ACTION ] Finish Cross-Validation
[ ACTION ] Clear the xLearn environment ...
[------------] Total time cost: 0.03 (sec)


Choose Optimization Method
----------------------------------------





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