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Equation (14.1) on page 513 defines the joint distribution represented by a Bayesian network in terms of the parameters θ(Xi |Parents(Xi)). This exercise asks you to derive the equivalence between the parameters and the conditional probabilities 𝐏(Xi |Parents(Xi)) from this definition. a. Consider a simple network X →Y →Z with three Boolean variables. Use Equations (13.3) and (13.6) (pages 485 and 492) to express the conditional probability P(z |y) as the ratio of two sums, each over entries in
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