Using evolutionary programming and minimum description length principle for data mining of Bayesian networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian networks, Evolutionary computation, Genetic algorithms, Minimum description length principle, Unsupervised learning
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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