How best attribute is selected in a decision tree? Select the root attribute of the decision tree from the given sample data.
Solutions
a) Entropy using the frequency table of one attribute:
b) Entropy using the frequency table of two attributes:
Information Gain: The information gain is based on the decrease in entropy after a data set is split on an attribute. Constructing a decision tree is all about finding
an attribute that returns the highest information gain (i.e., the most homogeneous
branches).