# Conditional Probability Network Instance

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A conditional probability network instance, [math]\displaystyle{ 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.**Context:**- 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.
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**Example(s):****Counter-Example(s):****See:**Hidden Markov Network.