Question: The following dataset contains some example data items with 3 categorical features x1 (classes A and B), x2 (classes C,D, and E ), x3 (classes

The following dataset contains some example data items with 3 categorical features x1 (classes A and B), x2 (classes C,D, and E ), x3 (classes F and G ) and label y (classes P, Q, and R). Apply the ID3 algorithm to build a decision tree. Show your work including the calculated entropy values, the information gain values, and the resulting decision tree. In case of a tie, select the first of the candidate features for splitting
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