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.[1] A Markov blanket can be constituted by a set of Markov chains.
^Pearl, Judea (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Representation and Reasoning Series. San Mateo CA: Morgan Kaufmann. ISBN 0-934613-73-7.
called a Markovblanket. If a Markovblanket is minimal, meaning that it cannot drop any variable without losing information, it is called a Markov boundary...
The Markovblanket of a node is the set of nodes consisting of its parents, its children, and any other parents of its children. The Markovblanket renders...
statistics. Causal Markov condition Chapman–Kolmogorov equation Hysteresis MarkovblanketMarkov chain Markov decision process Markov model Markov, A. A. (1954)...
A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on...
conditionally independent of the entire network, given its Markovblanket. The related Causal Markov (CM) condition states that, conditional on the set of...
hidden Markov-models combined with wavelets and the Markov-chain mixture distribution model (MCM). Markov chain Monte Carlo Markovblanket Andrey Markov Variable-order...
Markovblanket. More formally, the free energy principle says that if a system has a "particular partition" (i.e., into particles, with their Markov blankets)...
energy principle, the statistical manifold in question possesses a Markovblanket. Unsolved problem in computer science: How do global codes emerge from...
feature selection problem is the Markovblanket of the target node, and in a Bayesian Network, there is a unique MarkovBlanket for each node. There are different...
recapture Markov additive process MarkovblanketMarkov chain Markov chain geostatistics Markov chain mixing time Markov chain Monte Carlo Markov decision...
graph in which each node of the original G is now connected to its Markovblanket. The name stems from the fact that, in a moral graph, two nodes that...
Bayesian statisticsPages displaying wikidata descriptions as a fallback Markovblanket – Subset of variables that contains all the useful information Polytree –...
approximate distribution at each node through messages in the node's Markovblanket. Given some set of hidden variables H {\displaystyle H} and observed...
Markov additive process Markovblanket / Bay Markov chain mixing time / (L:D) Markov decision process Markov information source Markov kernel Markov logic...
ISBN 978-3-540-44139-7. Zexuan Zhu, Y. S. Ong and M. Dash (2007). "MarkovBlanket-Embedded Genetic Algorithm for Gene Selection". Pattern Recognition...
to visit all the vertices). Let P(x, y) be the transition kernel of the Markov chain given by a random walk on a finite graph G(V, E). Let U be a fixed...
security forces. He is the brother of Queen Ilona DeLamb-Markov and brother-in-law of King Viktor Markov of Markovia. He ran a meta-human trafficking ring under...
independently developed by Li, Mau, and Rannala and Yang and all using MCMC (Markov chain-Monte Carlo). 1998, TNT (Tree Analysis Using New Technology), Goloboff...
Griffin, Rob (2001). Chieftain. The Crowood Press, Ramsbury. Hull, Andrew W; Markov, David R.; Zaloga, Steven J. (2000). Soviet/Russian Armor and Artillery...