Conditional Probability Network Instance
A conditional probability network instance, [math]P(X|Y_1,...,Y_n)[/math], is a probabilistic network whose edges represent conditional probabilities such that the conditional probability of a node given all other nodes are equivalent to the conditional probability with all of its neighboring nodes
- AKA: Conditional Probabilistic Graphical Model.
- It can be a compact representation of joint probabilities.
- It can be used for Statistical Inference (to infer the Joint Probability Value for an Unobserved Random Variable given an Observed Random Variable).
- It can be used to represent Domain Knowledge.
- It can conform to a Conditional Probabilistic Graphical Metamodel.
- It can range from being an Undirected Conditional Probability Network to being a Directed Conditional Probability Network.
- It can (typically) be treated as a Discriminative Model.
- See: Hidden Markov Network.