Keywords

#markov_blanket

Markov blanket

Subset of variables that contains all the useful information

In statistics and machine learning, when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless. Such a subset that contains all the useful information is called a Markov blanket. If a Markov blanket is minimal, meaning that it cannot drop any variable without losing information, it is called a Markov boundary. Identifying a Markov blanket or a Markov boundary helps to extract useful features. The terms of Markov blanket and Markov boundary were coined by Judea Pearl in 1988. A Markov blanket can be constituted by a set of Markov chains.

Wed 15th

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Markov blanket Bayesian network Markov chain Markov property Causal Markov condition Markov model Andrey Markov Dependency network (graphical model) Free energy principle List of things named after Andrey Markov
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