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K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data

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1 Author(s)
Faulkner, E. ; Quantum Leap Innovations, Newark, DE

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

Published in:

Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on

Date of Conference:

March 1 2007-April 5 2007