Using evolutionary programming and minimum description length principle for data mining of Bayesian networks

Man Leung WONG, Wai LAM, Kwong Sak LEUNG

Research output: Journal PublicationsJournal Article (refereed)

82 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)174-178
Number of pages5
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number2
Publication statusPublished - 1 Jan 1999



  • Bayesian networks
  • Evolutionary computation
  • Genetic algorithms
  • Minimum description length principle
  • Unsupervised learning

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