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2. [25 pts] Classification. Use the training dataset in the following figure to learn a decision tree, which predicts the blue class or red class for each data point. a) [10 Points] Draw a decision tree with the above decision boundaries for the given training data set. b) [ 5 Points] Calculate the training error. c) [10 Points] Calculate the test error for the following test data set {D1,,D10}. D1 (3+x1,7) Class blue D2 (2+x2,9) Class red D3 (1+x3,1) Class blue D4 (2+x4,2) Class red D5 (6+x5,1) Class blue D6 (6+x6,10) Class red D7 (2+x7,7) Class blue D8 (4+x7,4) Class red D9 (3.5+x7,3.5) Class blue D10 (2.5+x7,2.5) Class red