Classification can be done using classification rules, which have a condition, a class, and a confidence; the confidence is the percentage of the inputs satisfying the condition that fall in the specified class. For example, a classification rule for credit ratings may have a condition that salary is between $30,000 and $50,000, and education level is graduate, with the credit rating class of good, and a confidence of 80%. A second rule may have a condition that salary is between $30,000 and $50,000, and education level is high-school, with the credit rating class of satisfactory, and a confidence of 80%. A third rule may have a condition that salary is above $50,001, with the credit rating class of excellent, and confidence of 90%. Show a decision tree classifier corresponding to the above rules. Show how the decision tree classifier can be extended to record the confidence values.