In this paper, we propose a more efficient Bayesian network structure learning algorithm under the framework of score based local learning （SLL）. Our algorithm significantly improves computational efficiency by rest...In this paper, we propose a more efficient Bayesian network structure learning algorithm under the framework of score based local learning （SLL）. Our algorithm significantly improves computational efficiency by restricting the neighbors of each variable to a small subset of candidates and storing necessary information to uncover the spouses, at the same time guaranteeing to find the optimal neighbor set in the same sense as SLL. The algorithm is the- oretically sound in the sense that it is optimal in the limit of large sample size. Empirical results testify its improved speed without loss of quality in the learned structures.展开更多
文摘In this paper, we propose a more efficient Bayesian network structure learning algorithm under the framework of score based local learning （SLL）. Our algorithm significantly improves computational efficiency by restricting the neighbors of each variable to a small subset of candidates and storing necessary information to uncover the spouses, at the same time guaranteeing to find the optimal neighbor set in the same sense as SLL. The algorithm is the- oretically sound in the sense that it is optimal in the limit of large sample size. Empirical results testify its improved speed without loss of quality in the learned structures.
