Visualizing decision tree in scikit-learn

Question

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 follo

Answer 1

Scikit learn recently introduced the plot_tree method to make this very easy (new in version 0.21 (May 2019)). Documentation here.

Here's the minimum code you need:

from sklearn import tree
plt.figure(figsize=(40,20))  # customize according to the size of your tree
_ = tree.plot_tree(your_model_name, feature_names = X.columns)
plt.show()

plot_tree supports some arguments to beautify the tree. For example:

from sklearn import tree
plt.figure(figsize=(40,20))  
_ = tree.plot_tree(your_model_name, feature_names = X.columns, 
             filled=True, fontsize=6, rounded = True)
plt.show()

If you want to save the picture to a file, add the following line before plt.show():

plt.savefig('filename.png')

If you want to view the rules in text format, there's an answer here. It's more intuitive to read.