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Y No. of Class C1 Examples No. of Class C2 Examples 10 0. 15 25 1 40 1 0. 10 0. 20 1 1 45 1 1 0. 15 Question 2: Consider the following set of training examples. a) Compute a two-level decision tree using the greedy approach. Use the classification error rate as the criterion for splitting. What is the overall error rate of the induced tree? b) Repeat part (a) using X as the first splitting attribute and then choose the best remaining attribute for splitting at cach of the two successor nodes. What is the error rate of the induced tree? c) Compare the results of parts (a) and (b). Comment on the suitability of the greedy heuristic used for splitting attribute selection. 010 201 0071

Y No. of Class C1 Examples No. of Class C2 Examples 10 0. 15 25 1 40 1 0. 10 0. 20 1 1 45 1 1 0. 15 Question 2: Consider the following set of training examples. a) Compute a two-level decision tree using the greedy approach. Use the classification error rate as the criterion for splitting. What is the overall error rate of the induced tree? b) Repeat part (a) using X as the first splitting attribute and then choose the best remaining attribute for splitting at cach of the two successor nodes. What is the error rate of the induced tree? c) Compare the results of parts (a) and (b). Comment on the suitability of the greedy heuristic used for splitting attribute selection. 010 201 0071

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Y No. of Class C1 Examples No. of Class C2 Examples 0. 10 0. 0. 15 25 1 40 1 0. 10 1 1 45 0. 0. 20 1 1 0. 15 Question 2: Consider the following set of training examples. a) Compute a two-level decision tree using the greedy approach. Use the classification error rate as the criterion for splitting. What is the overall error rate of the induced tree? b) Repeat part (a) using X as the first splitting attribute and then choose the best remaining attribute for splitting at cach of the two successor nodes. What is the error rate of the induced tree? c) Compare the results of parts (a) and (b). Comment on the suitability of the greedy heuristic used for splitting attribute selection. 010 0011 0011
Transcribed Image Text:Y No. of Class C1 Examples No. of Class C2 Examples 0. 10 0. 0. 15 25 1 40 1 0. 10 1 1 45 0. 0. 20 1 1 0. 15 Question 2: Consider the following set of training examples. a) Compute a two-level decision tree using the greedy approach. Use the classification error rate as the criterion for splitting. What is the overall error rate of the induced tree? b) Repeat part (a) using X as the first splitting attribute and then choose the best remaining attribute for splitting at cach of the two successor nodes. What is the error rate of the induced tree? c) Compare the results of parts (a) and (b). Comment on the suitability of the greedy heuristic used for splitting attribute selection. 010 0011 0011
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