Question

a) Given the decision tree and datasets as above, the generalization error rate of the tree using the optimistic approach is (value only, 1 decimal point)

b) Given the decision tree and datasets as above, the generalization error rate of the tree using the pessimistic approach (simply use the strategy of adding a factor of 0.5 to each leaf node) is: (value only, 1 decimal point)

c) Given the decision tree and datasets as above, the accuracy of the tree using the validation set is: (value only, 1 decimal point)

Answer 1

Answer:

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Explanation:

Answer 2

Answer:

A)The generalization error rate of the tree using the optimistic approach is ($0.3$

B)The generalization error rate of the tree using the pessimistic approach (simply use the strategy of adding a factor of 0.5 to each leaf node) is:$0.5$

C)The accuracy of the tree using the validation set is $0.8$

Explanation:

a) The question asks me to calculate generalization error rate by using optimistic and pessimistic approaches, and the answers are 0.3 and 0.5 respectively. They are totally different from my answers 0.5 and 0.7. From my calculation, instances 3, 7, 8, 9, 10 are misclassifications. I have searched many documentations on Google, and all of them didn't explain why and just showed that 3 / 10 = 0.3

b)

The total number of leaf nodes is N = 4, so our pessimistic estimate of the generalization error rate is:

$\frac{3 + 4 * 0.5}{10}\\= \frac{5}{10}\\ =0.5$

c) These are the classifications from the decision tree. This

approach is known as reduced error pruning. From this, we see that the generalization error rate is

$\frac{4}{5} =0.8$

Reference Link

• https://brainly.in/question/2942661
• https://brainly.in/question/48587942