Bayesian (Belief) Network: Difference between revisions
Myriad-admin (talk | contribs) Created page with "'''Definition''' Graphical models that communicate causal information and provide a framework for describing and evaluating probabilities when we have a network of interrelated variables. A key feature of Bayesian Belief Networks (or simply Bayesian Networks) is that they discover and describe causality rather than merely identifying associations. '''Source''' McClean, S.I. (2003). Data Mining and Knowledge Discovery. In Meyers R.A. (Eds.) Encyclopedia of Physical S..." |
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Graphical models that communicate causal information and provide a framework for describing and evaluating probabilities when we have a network of interrelated variables. | Graphical models that communicate causal information and provide a framework for describing and evaluating probabilities when we have a network of interrelated variables. | ||
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McClean, S.I. (2003). Data Mining and Knowledge Discovery. In Meyers R.A. (Eds.) Encyclopedia of Physical Science and Technology (Third Edition), 229-246 | McClean, S.I. (2003). Data Mining and Knowledge Discovery. In Meyers R.A. (Eds.) Encyclopedia of Physical Science and Technology (Third Edition), 229-246 | ||
Back to '''[[Definitions]]''' | Back to '''[[Definitions]]''' | ||
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Latest revision as of 11:56, 22 July 2022
Definition
Graphical models that communicate causal information and provide a framework for describing and evaluating probabilities when we have a network of interrelated variables.
A key feature of Bayesian Belief Networks (or simply Bayesian Networks) is that they discover and describe causality rather than merely identifying associations.
Source
McClean, S.I. (2003). Data Mining and Knowledge Discovery. In Meyers R.A. (Eds.) Encyclopedia of Physical Science and Technology (Third Edition), 229-246
Back to Definitions