Problem 6 (22 points) Information Gain and Split PlansConsider the following data set for a binary class problem. Illustrate your work/math to calculate the classification error rate when splitting on A and B.Which attribute would the decision tree induction algorithm choose? The definition ofmisclassification error is: (5 Points) The overall misclassification error before splitting: (5 Points) The gain in misclassification error after splitting on A: (5 Points) The gain in misclassification error after splitting on B: (3 Points) Which attribute would the decision tree choose: (4 Points) There are three impurity measurements: entropy, misclassification error, and Giniindex. Which one is the best for measuring impurity, and why?
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