Practice Questions
1. Given the decision tree in the figure below, the node 1
was split using feature A. Now suppose we wish to split
node 3. What is the feature that you will be using to split?
Show your work.
Practice Questions
2. Consider the following table showing bank loan decisions
for 10 customers. Answer the following questions:
Practice Questions
2 (a) We wish to build a decision tree to help decide if we
should approve or not the credit for new customers. Draw
the decision tree that fits this data and show how to
calculate each node split using entropy as the impurity
measure.
Note: If the entropy is the same for two or more features,
you can select any of the features to split.
2 (b) Based on the decision tree, given a new customer
with 51 years old, $120K annual income, that own a
house, should you approve the customer credit?