Visualise Decision Tree

VizTree.py

# visualise the decision tree

from sklearn.externals.six import StringIO  
from IPython.display import Image  
from sklearn.tree import export_graphviz
import pydotplus
dot_data = StringIO()

# ensure that variable tree has the decision tree, and features contains the names of the features
export_graphviz(tree,
                out_file=dot_data,
                feature_names = features,
                class_names = ['low','medium','high'],
                filled=True, rounded=True,
                special_characters=True)

graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
Image(graph.create_png())