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?
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()
...