+1 vote
in Artificial Intelligence by
What are Bayesian Networks?

2 Answers

0 votes
by

A Bayesian network is a statistical model that represents a set of variables and their conditional dependencies in the form of a directed acyclic graph. On the occurrence of an event, Bayesian Networks can be used to predict the likelihood that any one of several possible known causes was the contributing factor.

For example, a Bayesian network could be used to study the relationship between diseases and symptoms. Given various symptoms, the Bayesian network is ideal for computing the probabilities of the presence of various diseases.

0 votes
by

Bayesian Networks also referred to as 'belief networks' or 'casual networks', are used to represent the graphical model for probability relationship among a set of variables.

For example, a Bayesian network can be used to represent the probabilistic relationships between diseases and symptoms. As per the symptoms, the network can also compute the probabilities of the presence of various diseases.

Efficient algorithms can perform inference or learning in Bayesian networks. Bayesian networks which relate the variables (e.g., speech signals or protein sequences) are called dynamic Bayesian networks.

Related questions

0 votes
asked Oct 23, 2021 in Artificial Intelligence by DavidAnderson
0 votes
asked Oct 23, 2021 in Artificial Intelligence by DavidAnderson
...