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8. Consider the decision tree shown in Figure 4.30. (a) Compute the generalization error rate of the tree using the optimistic approach. (b) Compute the generalization error rate of the tree using the pessimistic approach. (For simplicity, use the strategy of adding a factor of 0.5 to each leaf node.) (c) Compute the generalization error rate of the tree using the validation set shown above. This approach is known as reduced error pruning. B Training: Instance A 1 0 2 0 A 3 0 1 4 0 1 5 1 6 1 7 1 1 8 1 9 1 1 000 B007700707 C Class 0 + 1 + 0 + 1 - + + - 1 + 10 1 1 lolo - - + + Validation: Instance A 11 COT BO с Class 0 + 12 0 1 1 + 13 1 1 0 + 14 1 15 1 0 OC 0 1 - 0 +

8. Consider the decision tree shown in Figure 4.30. (a) Compute the generalization error rate of the tree using the optimistic approach. (b) Compute the generalization error rate of the tree using the pessimistic approach. (For simplicity, use the strategy of adding a factor of 0.5 to each leaf node.) (c) Compute the generalization error rate of the tree using the validation set shown above. This approach is known as reduced error pruning. B Training: Instance A 1 0 2 0 A 3 0 1 4 0 1 5 1 6 1 7 1 1 8 1 9 1 1 000 B007700707 C Class 0 + 1 + 0 + 1 - + + - 1 + 10 1 1 lolo - - + + Validation: Instance A 11 COT BO с Class 0 + 12 0 1 1 + 13 1 1 0 + 14 1 15 1 0 OC 0 1 - 0 +

EBK ELECTRICAL WIRING RESIDENTIAL
EBK ELECTRICAL WIRING RESIDENTIAL
19th Edition
ISBN:9781337516549
Author:Simmons
Publisher:Simmons
Chapter29: Service-entrance Calculations
Section: Chapter Questions
Problem 3R: a. What is the ampere rating of the circuits that are provided for the small-appliance loads? _____...
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8. Consider the decision tree shown in Figure 4.30. (a) Compute the generalization error rate of the tree using the optimistic approach. (b) Compute the generalization error rate of the tree using the pessimistic approach. (For simplicity, use the strategy of adding a factor of 0.5 to each leaf node.) (c) Compute the generalization error rate of the tree using the validation set shown above. This approach is known as reduced error pruning. B Training: Instance A 1 0 2 0 A 3 0 1 4 0 1 5 1 6 1 7 1 1 8 1 9 1 1 000 B007700707 C Class 0 + 1 + 0 + 1 - + + - 1 + 10 1 1 lolo - - + + Validation: Instance A 11 COT BO с Class 0 + 12 0 1 1 + 13 1 1 0 + 14 1 15 1 0 OC 0 1 - 0 +
Transcribed Image Text:8. Consider the decision tree shown in Figure 4.30. (a) Compute the generalization error rate of the tree using the optimistic approach. (b) Compute the generalization error rate of the tree using the pessimistic approach. (For simplicity, use the strategy of adding a factor of 0.5 to each leaf node.) (c) Compute the generalization error rate of the tree using the validation set shown above. This approach is known as reduced error pruning. B Training: Instance A 1 0 2 0 A 3 0 1 4 0 1 5 1 6 1 7 1 1 8 1 9 1 1 000 B007700707 C Class 0 + 1 + 0 + 1 - + + - 1 + 10 1 1 lolo - - + + Validation: Instance A 11 COT BO с Class 0 + 12 0 1 1 + 13 1 1 0 + 14 1 15 1 0 OC 0 1 - 0 +
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