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<div class="section" id="classification-of-text-documents">
<span id="example-document-classification-news20-py"></span><h1>Classification of text documents<a class="headerlink" href="#classification-of-text-documents" title="Permalink to this headline">¶</a></h1>
<p><strong>Python source code:</strong> <a class="reference download internal" href="../_downloads/document_classification_news20.py"><tt class="xref download docutils literal"><span class="pre">document_classification_news20.py</span></tt></a></p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">sklearn.datasets</span> <span class="kn">import</span> <span class="n">fetch_20newsgroups_vectorized</span>
<span class="kn">from</span> <span class="nn">sklearn.cross_validation</span> <span class="kn">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">lightning.classification</span> <span class="kn">import</span> <span class="n">CDClassifier</span>
<span class="kn">from</span> <span class="nn">lightning.classification</span> <span class="kn">import</span> <span class="n">LinearSVC</span>
<span class="kn">from</span> <span class="nn">lightning.classification</span> <span class="kn">import</span> <span class="n">SGDClassifier</span>
<span class="c"># Load News20 dataset from scikit-learn.</span>
<span class="n">bunch</span> <span class="o">=</span> <span class="n">fetch_20newsgroups_vectorized</span><span class="p">(</span><span class="n">subset</span><span class="o">=</span><span class="s">"all"</span><span class="p">)</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">bunch</span><span class="o">.</span><span class="n">data</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">bunch</span><span class="o">.</span><span class="n">target</span>
<span class="c"># Select a subset of the classes for faster training.</span>
<span class="n">ind</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">X</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">subset</span> <span class="o">=</span> <span class="n">y</span> <span class="o"><</span> <span class="mi">5</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">X</span><span class="p">[</span><span class="n">ind</span><span class="p">[</span><span class="n">subset</span><span class="p">]]</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">y</span><span class="p">[</span><span class="n">subset</span><span class="p">]</span>
<span class="c"># Train / test split.</span>
<span class="n">X_tr</span><span class="p">,</span> <span class="n">X_te</span><span class="p">,</span> <span class="n">y_tr</span><span class="p">,</span> <span class="n">y_te</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.75</span><span class="p">,</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span>
<span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">clfs</span> <span class="o">=</span> <span class="p">(</span><span class="n">CDClassifier</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="s">"squared_hinge"</span><span class="p">,</span>
<span class="n">penalty</span><span class="o">=</span><span class="s">"l2"</span><span class="p">,</span>
<span class="n">max_iter</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span>
<span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="n">LinearSVC</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span>
<span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
<span class="n">SGDClassifier</span><span class="p">(</span><span class="n">learning_rate</span><span class="o">=</span><span class="s">"constant"</span><span class="p">,</span>
<span class="n">alpha</span><span class="o">=</span><span class="mf">1e-3</span><span class="p">,</span>
<span class="n">max_iter</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span>
<span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">))</span>
<span class="k">for</span> <span class="n">clf</span> <span class="ow">in</span> <span class="n">clfs</span><span class="p">:</span>
<span class="k">print</span><span class="p">(</span><span class="n">clf</span><span class="o">.</span><span class="n">__class__</span><span class="o">.</span><span class="n">__name__</span><span class="p">)</span>
<span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_tr</span><span class="p">,</span> <span class="n">y_tr</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">clf</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X_te</span><span class="p">,</span> <span class="n">y_te</span><span class="p">))</span>
</pre></div>
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