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CS 6375>Midterm: CS 6375 Spring 2021 Solutions

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Midterm: CS 6375 Spring 2015 Solutions The exam is closed book. You are allowed a one-page cheat sheet. Answer the questions in the spaces provided on the question sheets. If you run out of room f ... or an answer, use an additional sheet (available from the instructor) and staple it to your exam. • NAME • UTD-ID if known Question Points Score Decision Trees 10 Linear Classifiers 10 Neural Networks 20 Support Vector Machines 10 Point Estimation 10 Naive Bayes 10 Instance Based Learning 10 Extra Credit: Linear Regression 20 Total: 100 1Spring 2015 Final, Page 2 of 16 March 26, 2015Spring 2015 Final, Page 3 of 16 March 26, 2015 Question 1: Decision Trees (10 points) Consider the training dataset given below. A, B, and C are the attributes and Y is the class variable. A B C Y 0 1 0 Yes 1 0 1 Yes 0 0 0 No 1 0 1 No 0 1 1 No 1 1 0 Yes (a) (2 points) Can you draw a decision tree having 100% accuracy on this training set? If you answer is yes, draw the decision tree in the space provided below. If your answer is no, explain why? Solution: No. Because Examples #2 and #4 have the same feature vector but different classes. (b) (3 points) Which attribute among A, B and C has the highest information gain? Explain your answer. Solution: IG(A) = H(3; 3) − 1 2H(2; 1) − 1 2H(2; 1) IG(B) = H(3; 3) − 12H(2; 1) − 1 2H(2; 1) IG(C) = H(3; 3) − 1 2H(2; 1) − 1 2H(2; 1) Therefore, all three attributes have the same information gain. [Show More]

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