Respuesta :
To characterize the joint likelihood of all random variables without feeling the Bayesian network is p(w | r) needs two parameters: one for r = 1 and one for r = 0, generic probability parameters are required. Two are needed in p(s | r).
What exactly is a Bayesian network?
- A popular category of probabilistic graphical models are Bayesian networks.
- They are made up of a structure and parameters. The structure, which expresses conditional dependencies and independencies among random variables linked to nodes, is a directed acyclic graph (DAG).
- A Bayesian network is a probabilistic graphical model that uses a directed acyclic graph to describe a set of variables and their conditional dependencies.
- When determining the chance that any one of a number of potential known causes contributed to an event that already happened, Bayesian networks excel.
- A Bayesian network, for instance, could depict the probability connections between diseases and symptoms.
To learn more Bayesian network, refer to:
https://brainly.com/question/14789231
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