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Using Evolutionary Programming and Minimum Description Length Principle for Data Mining of Bayesian Networks
February 1999 (vol. 21 no. 2)
pp. 174-178

Abstract—We have developed a new approach (MDLEP) to learning Bayesian network structures based on the Minimum Description Length (MDL) principle and Evolutionary Programming (EP). It employs a MDL metric, which is founded on information theory, and integrates a knowledge-guided genetic operator for the optimization in the search process.

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Index Terms:
Evolutionary computation, Bayesian networks, unsupervised learning, minimum description length principle, genetic algorithms.
Citation:
Man Leung Wong, Wai Lam, Kwong Sak Leung, "Using Evolutionary Programming and Minimum Description Length Principle for Data Mining of Bayesian Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 2, pp. 174-178, Feb. 1999, doi:10.1109/34.748825
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