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aksnzhy · Dec 6, 2017 · 77dbf6f · 77dbf6f
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diff --git a/_build/doctrees/environment.pickle b/_build/doctrees/environment.pickle
diff --git a/_build/doctrees/index.doctree b/_build/doctrees/index.doctree
diff --git a/_build/html/_sources/index.rst.txt b/_build/html/_sources/index.rst.txt
@@ -33,12 +33,13 @@ source code and build it locally. We will update the xLearn source code on pip w
 
     sudo pip install xlearn
 
-Now you can type the following script in python shell to check whether we install xLearn successfully:
+The installation process will take a while. And then you can type the following script in python 
+shell to check whether we install xLearn successfully:
 
 >>> import xlearn as xl
 >>> xl.hello()
 
-If you meet any installation problem, or you want to build the lastest code on github, or you want to 
+If you meet any installation problem, or you want to build the lastest code from github, or you want to 
 use the xLearn command line instead of the python API, you can see how to build xLearn from source code 
 in `Installation Guide`__.
 
@@ -69,9 +70,6 @@ This example shows how to use field-aware factorizations machine (ffm) to solve
 simple binary classification task. You can check out the demo data 
 (``small_train.txt`` and ``small_test.txt``) from the path ``demo/classification/criteo_ctr``
 
-Other Helpful Resources
---------------------------------------------
-
  .. __: install.html
  .. __: install.html
  .. __: command_line.html
@@ -80,6 +78,7 @@ Other Helpful Resources
  .. __: tutorial.html
 
  .. toctree::
+   :hidden:
 
    install.rst
    command_line.rst

diff --git a/_build/html/index.html b/_build/html/index.html
@@ -187,12 +187,13 @@ <h2>Quick Install<a class="headerlink" href="#quick-install" title="Permalink to
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">pip</span> <span class="n">install</span> <span class="n">xlearn</span>
 </pre></div>
 </div>
-<p>Now you can type the following script in python shell to check whether we install xLearn successfully:</p>
+<p>The installation process will take a while. And then you can type the following script in python
+shell to check whether we install xLearn successfully:</p>
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">xlearn</span> <span class="k">as</span> <span class="nn">xl</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">xl</span><span class="o">.</span><span class="n">hello</span><span class="p">()</span>
 </pre></div>
 </div>
-<p>If you meet any installation problem, or you want to build the lastest code on github, or you want to
+<p>If you meet any installation problem, or you want to build the lastest code from github, or you want to
 use the xLearn command line instead of the python API, you can see how to build xLearn from source code
 in <a class="reference external" href="tutorial.html">Installation Guide</a>.</p>
 </div>
@@ -219,38 +220,8 @@ <h2>Python Demo<a class="headerlink" href="#python-demo" title="Permalink to thi
 <p>This example shows how to use field-aware factorizations machine (ffm) to solve a
 simple binary classification task. You can check out the demo data
 (<code class="docutils literal"><span class="pre">small_train.txt</span></code> and <code class="docutils literal"><span class="pre">small_test.txt</span></code>) from the path <code class="docutils literal"><span class="pre">demo/classification/criteo_ctr</span></code></p>
-</div>
-<div class="section" id="other-helpful-resources">
-<h2>Other Helpful Resources<a class="headerlink" href="#other-helpful-resources" title="Permalink to this headline">¶</a></h2>
 <blockquote>
 <div><div class="toctree-wrapper compound">
-<ul>
-<li class="toctree-l1"><a class="reference internal" href="install.html">Installation Guide</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="install.html#install-gcc-or-clang">Install GCC or Clang</a></li>
-<li class="toctree-l2"><a class="reference internal" href="install.html#install-cmake">Install CMake</a></li>
-<li class="toctree-l2"><a class="reference internal" href="install.html#install-xlearn-from-pip">Install xLearn from pip</a></li>
-<li class="toctree-l2"><a class="reference internal" href="install.html#install-xlearn-from-source-code">Install xLearn from source code</a><ul>
-<li class="toctree-l3"><a class="reference internal" href="install.html#build-c-code">Build C++ code</a></li>
-<li class="toctree-l3"><a class="reference internal" href="install.html#install-python-package">Install python package</a><ul class="simple">
-</ul>
-</li>
-</ul>
-</li>
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="command_line.html">xLearn Command Line Guide</a><ul class="simple">
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="python_api.html">xLearn Python API Guide</a><ul class="simple">
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="demo.html">xLearn Demo</a><ul class="simple">
-</ul>
-</li>
-<li class="toctree-l1"><a class="reference internal" href="tutorial.html">xLearn Tutorials</a><ul class="simple">
-</ul>
-</li>
-</ul>
 </div>
 </div></blockquote>
 </div>

diff --git a/_build/html/searchindex.js b/_build/html/searchindex.js
diff --git a/index.rst b/index.rst
@@ -33,12 +33,13 @@ source code and build it locally. We will update the xLearn source code on pip w
 
     sudo pip install xlearn
 
-Now you can type the following script in python shell to check whether we install xLearn successfully:
+The installation process will take a while. And then you can type the following script in python 
+shell to check whether we install xLearn successfully:
 
 >>> import xlearn as xl
 >>> xl.hello()
 
-If you meet any installation problem, or you want to build the lastest code on github, or you want to 
+If you meet any installation problem, or you want to build the lastest code from github, or you want to 
 use the xLearn command line instead of the python API, you can see how to build xLearn from source code 
 in `Installation Guide`__.
 
@@ -69,9 +70,6 @@ This example shows how to use field-aware factorizations machine (ffm) to solve
 simple binary classification task. You can check out the demo data 
 (``small_train.txt`` and ``small_test.txt``) from the path ``demo/classification/criteo_ctr``
 
-Other Helpful Resources
---------------------------------------------
-
  .. __: install.html
  .. __: install.html
  .. __: command_line.html
@@ -80,6 +78,7 @@ Other Helpful Resources
  .. __: tutorial.html
 
  .. toctree::
+   :hidden:
 
    install.rst
    command_line.rst