Definitions for **"Bayesian network"**

A technology used to model domain knowledge containing uncertainty - the core technology for building Hugin Knowledge Bases

a compact, expressive representation of uncertain relationships among parameters in a domain

a directed acyclic graph (DAG) rep resentation of the joint probability distribution for a set of random variables Horvitz et al

a Directed Acyclic Graph (DAG) where graph nodes represent variables

a directed acyclic graph in which each node

a directed acyclic graph that represents a factorization of a probability distribution

a directed graphical representation of probabilistic relationships that people find easy to understand and use, often because the relationships have a causal interpretation

a directed graph whose nodes represent random variables

a graphical model for probabilistic relationships among a set of variables

a graphical model for reasoning under uncertainty

a graphical model that encodes probabilistic relationships among variables of interest

a graph of relationships among variables in a data set

a high-level representation of a probability distribution over a set of variables that are used for building a model of the problem domain

a knowledge representation technique for use in expert system development

a modeling technique that provides a mathematically sound formula for representing and reasoning uncertainty, imprecision, or unpredictability in our knowledge

a model of cause and effect, consistent with the conditional independencies embedded within the overall probability density function

an annotated directed acyclic graph encoding a joint probability distribution

an efficient way to encode uncertain knowledge in a way which allows proper reasoning under that uncertainty

a probabilistic representation for uncertain relationships, which has proven to be useful for modeling real-world problems

a representation of the joint distribution over all the variables represented by nodes in the graph

a representation of the probabilistic relationships among distinctions about the world

A directed graph that that can be used to reason with probabilistic information.

(BN) A directed, acyclic graph in which nodes represent stochastic variables (either continuous variables or with discrete states) and the edges represent probabilistic influences (represented as conditional probabilities).

A bayesian network (or a belief network) is a directed acyclic graph which represents independencies embodied in a given joint probability distribution over a set of variables. Nodes can represent any kind of variable, be it a measured parameter, a latent variable or a hypothesis. They are not restricted to representing random variables; which forms the "Bayesian" aspect of a Bayesian network.