### Artificial IntelligenceAIMA Exercises

Suppose that in a Bayesian network containing an unobserved variable $Y$, all the variables in the Markov blanket ${MB}(Y)$ have been observed.
1. Prove that removing the node $Y$ from the network will not affect the posterior distribution for any other unobserved variable in the network.
2. Discuss whether we can remove $Y$ if we are planning to use (i) rejection sampling and (ii) likelihood weighting.

Suppose that in a Bayesian network containing an unobserved variable $Y$, all the variables in the Markov blanket ${MB}(Y)$ have been observed.
1. Prove that removing the node $Y$ from the network will not affect the posterior distribution for any other unobserved variable in the network.
2. Discuss whether we can remove $Y$ if we are planning to use (i) rejection sampling and (ii) likelihood weighting.

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