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CIDM
2007
IEEE

K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data

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K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified version of the K2 heuristic to score proposed networks and improve future generations. We show each component of K2GA, a combination of these components to form the basic algorithm, extensions to the algorithm for improved accuracy, and numerical results.
Eli Faulkner
Added 02 Jun 2010
Updated 02 Jun 2010
Type Conference
Year 2007
Where CIDM
Authors Eli Faulkner
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