Given the Bayesian network shown in Figure 5.48, compute the following probabilities:

Consider the one-dimensional data set shown in Table 5.13.

(a) Demonstrate how the perceptron model can be used to represent the AND and OR functions between a pair of Boolean variables.

GYou are ased to evaluate the performance of two classification models, M1 and M2. The test set you have chosen contains 26 binary attributes, labeled as A through Z.

Table 5.14 shows the posterior probabilities obtained by applying the models to the test set. (Only the posterior probabilities for the positive class are shown). As this is a two-class problem, P(-) = 1 - P(+) and P(-|A, ..., Z). Assume that we are mostly interested in detecting instances from the positive class.

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