a) What is the size and dimensionality of the training set? (10), o obbob lliw b)...

  

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a) What is the size and dimensionality of the training set? (10), o obbob lliw b) What is the size and dimensionality of the test set? c) How many training instances are associated with the root node of DT1? 2 d) How many training instances are associated with the node of DT1 that you reach when A= 2? 3.2 [8 pts] Estimate the generalization error rate of both trees shown in Figure 1 (DT1, DT2) using the optimistic approach and the pessimistic approach. To account for model complexity with the pessimistic approach, use a penalty value of 22 for each leaf node. Table 5 3 9 Training set B # of (+) instances # of (-) instances 4 Test set # of (+) instances # of (-) instances 4 1 A 0 0 0 1 1 0 1 1 20 32718 22 2 1 3 4 7 30 6 4 46364 9 a) What is the size and dimensionality of the training set? (10), o obbob lliw b) What is the size and dimensionality of the test set? c) How many training instances are associated with the root node of DT1? 2 d) How many training instances are associated with the node of DT1 that you reach when A= 2? 3.2 [8 pts] Estimate the generalization error rate of both trees shown in Figure 1 (DT1, DT2) using the optimistic approach and the pessimistic approach. To account for model complexity with the pessimistic approach, use a penalty value of 22 for each leaf node. Table 5 3 9 Training set B # of (+) instances # of (-) instances 4 Test set # of (+) instances # of (-) instances 4 1 A 0 0 0 1 1 0 1 1 20 32718 22 2 1 3 4 7 30 6 4 46364 9