Causal Markov condition
Overview
Bayesian network
A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph . For example, a Bayesian network could represent the probabilistic...
states that any node in a Bayesian network is conditionally independent of its nondescendents, given its parents.
A node is conditionally independent of the entire network, given its Markov blanket
Markov blanket
In machine learning, the Markov blanket for a node A in a Bayesian network is the set of nodes \partial A composed of A's parents, its children, and its children's other parents. In a Markov network, the Markov blanket of a node is its set of neighbouring nodes...
.
The related causal Markov condition is that a phenomenon is independent of its noneffects, given its direct causes. In the event that the structure of a Bayesian network accurately depicts causality
Causality
Causality is the relationship between an event and a second event , where the second event is understood as a consequence of the first....
, the two conditions are equivalent.
