[FIXED] Visualizing decision tree in scikit-learn

Issue

I am trying to design a simple Decision Tree using scikit-learn in Python (I am using Anaconda's Ipython Notebook with Python 2.7.3 on Windows OS) and visualize it as follows:

from pandas import read_csv, DataFrame
from sklearn import tree
from os import system

data = read_csv('D:/training.csv')
Y = data.Y
X = data.ix[:,"X0":"X33"]

dtree = tree.DecisionTreeClassifier(criterion = "entropy")
dtree = dtree.fit(X, Y)

dotfile = open("D:/dtree2.dot", 'w')
dotfile = tree.export_graphviz(dtree, out_file = dotfile, feature_names = X.columns)
dotfile.close()
system("dot -Tpng D:.dot -o D:/dtree2.png")

However, I get the following error:

AttributeError: 'NoneType' object has no attribute 'close'

I use the following blog post as reference: Blogpost link

The following stackoverflow question doesn't seem to work for me as well: Question

Could someone help me with how to visualize the decision tree in scikit-learn?

Solution

sklearn.tree.export_graphviz doesn't return anything, and so by default returns None.

By doing dotfile = tree.export_graphviz(...) you overwrite your open file object, which had been previously assigned to dotfile, so you get an error when you try to close the file (as it's now None).

To fix it change your code to

...
dotfile = open("D:/dtree2.dot", 'w')
tree.export_graphviz(dtree, out_file = dotfile, feature_names = X.columns)
dotfile.close()
...

Answered By - Ffisegydd