There is a method to export to graph_viz format: http://scikit-learn.org/stable/modules/generated/sklearn.tree.export_graphviz.html
So from the online docs:
>>> 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')
Then you can load this using graph viz, or if you have pydot installed then you can do this more directly: http://scikit-learn.org/stable/modules/tree.html
>>> from sklearn.externals.six import StringIO
>>> import pydot
>>> dot_data = StringIO()
>>> tree.export_graphviz(clf, out_file=dot_data)
>>> graph = pydot.graph_from_dot_data(dot_data.getvalue())
>>> graph.write_pdf("iris.pdf")
Will produce an svg, can't display it here so you'll have to follow the link: http://scikit-learn.org/stable/_images/iris.svg
Update
It seems that there has been a change in the behaviour since I first answered this question and it now returns a list
and hence you get this error:
AttributeError: 'list' object has no attribute 'write_pdf'
Firstly when you see this it's worth just printing the object and inspecting the object, and most likely what you want is the first object:
graph[0].write_pdf("iris.pdf")
Thanks to @NickBraunagel for the comment
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