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Explain what Bayesian Belief Networks (BBNs) are and what they represent.
Explain what Bayesian Belief Networks (BBNs) are and what they represent.
BBNs are a type of probabilistic graphical model that represents the probabilistic relationships among a set of variables based on Bayesian probability theory.
What do the nodes and edges represent in a BBN?
What do the nodes and edges represent in a BBN?
Nodes represent random variables, and edges represent the relationships between variables, with a directed edge from variable A to variable B indicating that A has a direct influence on B.
What are Conditional Probability Tables (CPTs) in a BBN?
What are Conditional Probability Tables (CPTs) in a BBN?
Each node in a BBN has an associated CPT, which specifies the probability distribution of the node given its parents in the network.
What is the basis of Bayesian probability theory?
What is the basis of Bayesian probability theory?
What are some other names for Bayesian Belief Networks (BBNs)?
What are some other names for Bayesian Belief Networks (BBNs)?
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