Discovery of context-specific Markov blankets

The notion of context-specific Markov blankets (CSMB) is a refinement of Markov blankets (MB). An important property of context specific Markov-blankets is that in the worst case they need as many parameters as a model using a standard Markov blanket, but frequently considerably fewer. The result is...

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Bibliographic Details
Main Authors: Klein, A., Shimony, S.E.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Bayesian methods
Computer science
control theory
systems
Context modeling
Control theory. Systems
Data mining
Exact sciences and technology
Knowledge representation
Learning systems
Mathematics
Probability
Random variables
Robots
Topology
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Description
Summary:The notion of context-specific Markov blankets (CSMB) is a refinement of Markov blankets (MB). An important property of context specific Markov-blankets is that in the worst case they need as many parameters as a model using a standard Markov blanket, but frequently considerably fewer. The result is expected to be a much improved probabilistic model of the data in practice. An algorithm for discovery of the CSMB is presented, and empirical results show that it is capable of successfully recovering context specific (''local") structures.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2004.1400942