DBN Learning Algorithm Based on Evolutionary MCMC

Dynamic Bayesian Network(DBN) learning with evolutionary MCMC algorithm is presented.Parameter learning with absent data is done with EM algorithm.In structure learning,multiple Bayesian network chromosomes are generated as candidates and are processed with mutation and crossover.The structures are learned with MCMC function which is obtained with temperatures and Bayesian Information Criterion(BIC) scores of corresponding Bayesian networks.In each generation,the Bayesian network with the maximal BIC score is selected as the result of the structure learning.Experimental results proves the stability of the method's performance.