Calculating root entropy
This exercise continues with the loan default example from the slides. The image shows the root node of a decision tree split by color. In these next three exercises, you will calculate the entropy of the root node, calculate the entropy of the child nodes, and determine the information gain that color provides for determining loan default status.
In this exercise, the task is to calculate the entropy of the root node in this decision tree.
This exercise is part of the course
Dimensionality Reduction in R
Exercise instructions
- Calculate the class probabilities of "yes" and "no" classes in the root node for defaulting on a loan.
- Use the class probabilities to calculate the entropy of the root node.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate the class probabilities
p_yes <- ___
p_no <- ___
# Calculate the entropy
entropy_root <- -(___ * log2(p_yes)) +
-(___ * ___(___))
entropy_root