title: How to display decision tree plot using export_graphviz
body: <p><strong>NEWBIE</strong></p>
  
  <p>using microsoft version 10, python 3.5.2, dot - graphviz version 2.38.0 (correctly installed)</p>
  
  <p>trying to use export_graphviz to visualize a decision tree.
  think it is pretty close, just can't do the last step.</p>
  
  <p>here is the sample code</p>
  
  <pre><code>from sklearn.datasets import load_iris
  from sklearn import tree
  clf = tree.DecisionTreeClassifier()
  iris = load_iris()
  clf = clf.fit(iris.data, iris.target)
  tree.export_graphviz(clf, out_file='tree.dot')
  </code></pre>
  
  <p>`</p>
  
  <p>the 'tree.dot' file is output.  when double clicked, it calls up microsoft word and display the following text.</p>
  
  <pre><code>digraph Tree {
  node [shape=box] ;
  0 [label="X[2] &lt;= 2.45\ngini = 0.6667\nsamples = 150\nvalue = [50, 50, 50]"] ;
  1 [label="gini = 0.0\nsamples = 50\nvalue = [50, 0, 0]"] ;
  0 -&gt; 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
  2 [label="X[3] &lt;= 1.75\ngini = 0.5\nsamples = 100\nvalue = [0, 50, 50]"] ;
  0 -&gt; 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
  3 [label="X[2] &lt;= 4.95\ngini = 0.168\nsamples = 54\nvalue = [0, 49, 5]"] ;
  2 -&gt; 3 ;
  4 [label="X[3] &lt;= 1.65\ngini = 0.0408\nsamples = 48\nvalue = [0, 47, 1]"] ;
  3 -&gt; 4 ;
  5 [label="gini = 0.0\nsamples = 47\nvalue = [0, 47, 0]"] ;
  4 -&gt; 5 ;
  6 [label="gini = 0.0\nsamples = 1\nvalue = [0, 0, 1]"] ;
  4 -&gt; 6 ;
  7 [label="X[3] &lt;= 1.55\ngini = 0.4444\nsamples = 6\nvalue = [0, 2, 4]"] ;
  3 -&gt; 7 ;
  8 [label="gini = 0.0\nsamples = 3\nvalue = [0, 0, 3]"] ;
  7 -&gt; 8 ;
  9 [label="X[0] &lt;= 6.95\ngini = 0.4444\nsamples = 3\nvalue = [0, 2, 1]"] ;
  7 -&gt; 9 ;
  10 [label="gini = 0.0\nsamples = 2\nvalue = [0, 2, 0]"] ;
  9 -&gt; 10 ;
  11 [label="gini = 0.0\nsamples = 1\nvalue = [0, 0, 1]"] ;
  9 -&gt; 11 ;
  12 [label="X[2] &lt;= 4.85\ngini = 0.0425\nsamples = 46\nvalue = [0, 1, 45]"] ;
  2 -&gt; 12 ;
  13 [label="X[1] &lt;= 3.1\ngini = 0.4444\nsamples = 3\nvalue = [0, 1, 2]"] ;
  12 -&gt; 13 ;
  14 [label="gini = 0.0\nsamples = 2\nvalue = [0, 0, 2]"] ;
  13 -&gt; 14 ;
  15 [label="gini = 0.0\nsamples = 1\nvalue = [0, 1, 0]"] ;
  13 -&gt; 15 ;
  16 [label="gini = 0.0\nsamples = 43\nvalue = [0, 0, 43]"] ;
  12 -&gt; 16 ;
  }
  </code></pre>
  
  <p>this example code works properly</p>
  
  <blockquote>
    <p>[<a href="http://scikit-learn.org/stable/auto_examples/tree/plot_iris.html#sphx-glr-auto-examples-tree-plot-iris-py" rel="nofollow noreferrer">http://scikit-learn.org/stable/auto_examples/tree/plot_iris.html#sphx-glr-auto-examples-tree-plot-iris-py</a> ][1]</p>
  </blockquote>
  
  <p>thanks in advance</p>