Learning Dynamic Bayesian Networks Using Evolutionary MCMC

@article{Wang2006LearningDB,
  title={Learning Dynamic Bayesian Networks Using Evolutionary MCMC},
  author={Hao Wang and Kui Yu and Hongliang Yao},
  journal={2006 International Conference on Computational Intelligence and Security},
  year={2006},
  volume={1},
  pages={45-50}
}
The current algorithms of learning the structure of dynamic Bayesian networks attempt to find single "best" model. However, this approach ignores the uncertainty in model selection and is prone to overfitting and local optimal problem. Markov chain Monte Carlo algorithm based on Bayesian model averaging can provide a way for accounting for this model uncertainty, but the convergence is too slow. Therefore, in this paper, a novel method, called DBN-EMC algorithm, is proposed which integrates… CONTINUE READING
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