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<li><a class="reference internal" href="#">Plot different SVM classifiers in the iris dataset</a></li>
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  <div class="section" id="plot-different-svm-classifiers-in-the-iris-dataset">
<span id="example-svm-plot-iris-py"></span><h1>Plot different SVM classifiers in the iris dataset<a class="headerlink" href="#plot-different-svm-classifiers-in-the-iris-dataset" title="Permalink to this headline">ΒΆ</a></h1>
<p>Comparison of different linear SVM classifiers on the iris dataset. It
will plot the decision surface for four different SVM classifiers.</p>
<img alt="auto_examples/svm/images/plot_iris.png" class="align-center" src="auto_examples/svm/images/plot_iris.png" />
<p><strong>Python source code:</strong> <a class="reference download internal" href="../../_downloads/plot_iris.py"><tt class="xref download docutils literal"><span class="pre">plot_iris.py</span></tt></a></p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">print</span> <span class="n">__doc__</span>

<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pylab</span> <span class="kn">as</span> <span class="nn">pl</span>
<span class="kn">from</span> <span class="nn">scikits.learn</span> <span class="kn">import</span> <span class="n">svm</span><span class="p">,</span> <span class="n">datasets</span>

<span class="c"># import some data to play with</span>
<span class="n">iris</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">load_iris</span><span class="p">()</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">data</span><span class="p">[:,</span> <span class="p">:</span><span class="mi">2</span><span class="p">]</span> <span class="c"># we only take the first two features. We could</span>
                     <span class="c"># avoid this ugly slicing by using a two-dim dataset</span>
<span class="n">Y</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">target</span>

<span class="n">h</span><span class="o">=.</span><span class="mo">02</span> <span class="c"># step size in the mesh</span>

<span class="c"># we create an instance of SVM and fit out data. We do not scale our</span>
<span class="c"># data since we want to plot the support vectors</span>
<span class="n">svc</span>     <span class="o">=</span> <span class="n">svm</span><span class="o">.</span><span class="n">SVC</span><span class="p">(</span><span class="n">kernel</span><span class="o">=</span><span class="s">&#39;linear&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">fit</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">rbf_svc</span> <span class="o">=</span> <span class="n">svm</span><span class="o">.</span><span class="n">SVC</span><span class="p">(</span><span class="n">kernel</span><span class="o">=</span><span class="s">&#39;poly&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">fit</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">nu_svc</span>  <span class="o">=</span> <span class="n">svm</span><span class="o">.</span><span class="n">NuSVC</span><span class="p">(</span><span class="n">kernel</span><span class="o">=</span><span class="s">&#39;linear&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">fit</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">lin_svc</span> <span class="o">=</span> <span class="n">svm</span><span class="o">.</span><span class="n">LinearSVC</span><span class="p">()</span><span class="o">.</span><span class="n">fit</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="c"># create a mesh to plot in</span>
<span class="n">x_min</span><span class="p">,</span> <span class="n">x_max</span> <span class="o">=</span> <span class="n">X</span><span class="p">[:,</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">X</span><span class="p">[:,</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">+</span><span class="mi">1</span>
<span class="n">y_min</span><span class="p">,</span> <span class="n">y_max</span> <span class="o">=</span> <span class="n">X</span><span class="p">[:,</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">X</span><span class="p">[:,</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">+</span><span class="mi">1</span>
<span class="n">xx</span><span class="p">,</span> <span class="n">yy</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">meshgrid</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">x_min</span><span class="p">,</span> <span class="n">x_max</span><span class="p">,</span> <span class="n">h</span><span class="p">),</span>
                     <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">y_min</span><span class="p">,</span> <span class="n">y_max</span><span class="p">,</span> <span class="n">h</span><span class="p">))</span>

<span class="c"># title for the plots</span>
<span class="n">titles</span> <span class="o">=</span> <span class="p">[</span><span class="s">&#39;SVC with linear kernel&#39;</span><span class="p">,</span>
          <span class="s">&#39;SVC with polynomial (degree 3) kernel&#39;</span><span class="p">,</span>
          <span class="s">&#39;NuSVC with linear kernel&#39;</span><span class="p">,</span>
          <span class="s">&#39;LinearSVC (linear kernel)&#39;</span><span class="p">]</span>


<span class="n">pl</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">pl</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">Paired</span><span class="p">)</span>

<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">clf</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">((</span><span class="n">svc</span><span class="p">,</span> <span class="n">rbf_svc</span><span class="p">,</span> <span class="n">nu_svc</span><span class="p">,</span> <span class="n">lin_svc</span><span class="p">)):</span>
    <span class="c"># Plot the decision boundary. For that, we will asign a color to each</span>
    <span class="c"># point in the mesh [x_min, m_max]x[y_min, y_max].</span>
    <span class="n">pl</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">Z</span> <span class="o">=</span> <span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">c_</span><span class="p">[</span><span class="n">xx</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">yy</span><span class="o">.</span><span class="n">ravel</span><span class="p">()])</span>

    <span class="c"># Put the result into a color plot</span>
    <span class="n">Z</span> <span class="o">=</span> <span class="n">Z</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">xx</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
    <span class="n">pl</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">pl</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">Paired</span><span class="p">)</span>
    <span class="n">pl</span><span class="o">.</span><span class="n">contourf</span><span class="p">(</span><span class="n">xx</span><span class="p">,</span> <span class="n">yy</span><span class="p">,</span> <span class="n">Z</span><span class="p">)</span>
    <span class="n">pl</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s">&#39;tight&#39;</span><span class="p">)</span>

    <span class="c"># Plot also the training points</span>
    <span class="n">pl</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">X</span><span class="p">[:,</span><span class="mi">0</span><span class="p">],</span> <span class="n">X</span><span class="p">[:,</span><span class="mi">1</span><span class="p">],</span> <span class="n">c</span><span class="o">=</span><span class="n">Y</span><span class="p">)</span>

    <span class="n">pl</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">titles</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>

<span class="n">pl</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s">&#39;tight&#39;</span><span class="p">)</span>
<span class="n">pl</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
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