Structural Learning Of Bayesian Network By Multi-population Bacterial Foraging Optimization

The structural learning is the core of the Bayesian network learning. The study of Bayesian network structure from the sample data is NP-Hard problems, and the current mainstream approach is to combine the heuristic algorithm. The paper uses multi-population bacteria foraging optimization (MBFO) algorithm to study Bayesian network structural learning,. Finally, the algorithm is proved to be more effective in the standard Bayesian network Cancer network, Asia network, Car network than classical structural learning algorithm.