Bayesian Network, Bayesian Network

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

Efficient algorithms exist that perform inference and learning in Bayesian networks. Bayesian networks that model sequences of variables ( e.g.

In the numerator marginalizing over \mathit = 1024 values. If the local distributions of no variable depends on more than 3 parent variables, the Bayesian network representation only needs to store at most 10*2^3 = 80 values.

Source: Wikipedia > Bayesian Network