Q. In a Bayesian network variable is?

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Q. If we have variables x1, x2, x3,....., xn, then the probabilities of a different combination of x1, x2, x3.. xn, are known as?

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Q. The nodes and links form the structure of the Bayesian network, and we call this the ?

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Q. Which of the following are used for modeling times series and sequences?

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Q. How many terms are required for building a bayes model?

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Q. What does the bayesian network provides?

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Q. ____________ is the process of calculating a probability distribution of interest e.g. P(A | B=True), or P(A,B|C, D=True).

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Q. The Distributive law simply means that if we want to marginalize out the variable A we can perform the calculations on the subset of distributions that contain A.

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Q. Bayesian networks are a factorized representation of the full joint.

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Q. What is the consequence between a node and its predecessors while creating bayesian network?

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Q. Which condition is used to influence a variable directly by all the others?

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Q. To which does the local structure is associated?

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Q. When we query a node in a Bayesian network, the result is often referred to as the marginal.

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