pythondecision-treepydot

Python, PyDot and DecisionTree

I'm trying to visualize my DecisionTree, but getting the error The code is:

X = [i[1:] for i in dataset]#attribute
y = [i[0] for i in dataset]
clf = tree.DecisionTreeClassifier()

dot_data = StringIO()
tree.export_graphviz(clf.fit(train_X, train_y), out_file=dot_data)
graph = pydot.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("tree.pdf")

And the error is

Traceback (most recent call last):
if data.startswith(codecs.BOM_UTF8):
TypeError: startswith first arg must be str or a tuple of str, not bytes

Can anyone explain me whats the problem? Thank you a lot!

Solution

  • I had the same exact problem and just spent a couple hours trying to figure this out. I can't guarantee what I share here will work for others but it may be worth a shot.

    1. I tried installing official pydot packages but I have Python 3 and they simply did not work. After finding a note in a thread from one of the many websites I scoured through, I ended up installing this forked repository of pydot.
    2. I went to graphviz.org and installed their software on my Windows 7 machine. If you don't have Windows, look under their Download section for your system.
    3. After successful install, in Environment Variables (Control Panel\All Control Panel Items\System\Advanced system settings > click Environment Variables button > under System variables I found the variable path > click Edit... > I added ;C:\Program Files (x86)\Graphviz2.38\bin to the end in the Variable value: field.
    4. To confirm I can now use dot commands in the Command Line (Windows Command Processor), I typed dot -V which returned dot - graphviz version 2.38.0 (20140413.2041).

    In the below code, keep in mind that I'm reading a dataframe from my clipboard. You might be reading it from file or whathaveyou.

    In IPython Notebook:

    import pandas as pd
import numpy as np
from sklearn import tree
import pydot
from IPython.display import Image
from sklearn.externals.six import StringIO

df = pd.read_clipboard()
X = df[df.columns[:-1]]
y = df[df.columns[-1]]

dtr = tree.DecisionTreeRegressor(max_depth=3)
dtr.fit(X, y)

dot_data = StringIO()  
tree.export_graphviz(dtr, out_file=dot_data, feature_names=X.columns)  
graph = pydot.graph_from_dot_data(dot_data.getvalue())  
Image(graph.create_png())

    Decision Tree Visualization

    Alternatively, if you're not using IPython, you can generate your own image from the command line as long as you have graphviz installed (step 2 above). Using my same example code above, you use this line after fitting the model:

    tree.export_graphviz(dtr.tree_, out_file='treepic.dot', feature_names=X.columns)

    then open up command prompt where the treepic.dot file is and enter this command line:

    dot -T png treepic.dot -o treepic.png

    A .png file should be created with your decision tree.