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YU Peng, LIU Dayou, JIA Haiyang, YANG Bo
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Abstract: A new algorithm was put forward for learning Bayesian’s network structure. This algorithm is based on an improved Genetic Algorithm: Immune Evolutionary Algorithm (IEA). The IEA combines the two kinds of methods in learning’s Bayesian network, the score based method and the constraint based method, by genetic operation and vaccination operation. The experimental results show that the convergent speed of IEA is more rapid, and the precision of IEA is higher than that of EGA (Expectation & Genetic Algorithm, a method learning Bayesian network based on GA).
Key words: Bayesian network, immune evolutionary algorithm, genetic algorithm
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YU Peng, LIU Dayou, JIA Haiyang, YANG Bo. Learning Bayesian Network Structure Based on Immune Evolutionary Algorithms[J].J4, 2006, 44(06): 919-924.
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URL: http://xuebao.jlu.edu.cn/lxb/EN/
http://xuebao.jlu.edu.cn/lxb/EN/Y2006/V44/I06/919
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