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【ML】Markov Network

【ML】Markov Network

作者: 盐果儿 | 来源:发表于2022-08-23 21:44 被阅读0次

What is markov network?

Definition

In the domain of physics and probability, a Markov random field (MRF), Markov network or undirected graphical model is a set of random variables having a Markov property described by an undirected graph. In other words, a random field is said to be a Markov random field if it satisfies Markov properties. The concept originates from the Sherrington–Kirkpatrick model.

A markov network or MRF is similar to a Bayesian network in its representation of dependencies; the differences being that Bayesian networks are directed and acyclic, whereas Markov networks are undirected and may be cyclic. Thus, a Markov network can represent certain dependencies that a Bayesian network cannot (such as cyclic dependencies[further explanation needed]); on the other hand, it can't represent certain dependencies that a Bayesian network can (such as induced dependencies[further explanation needed]). The underlying graph of a Markov random field may be finite or infinite.

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