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中文摘要：
针对I-B＆B-MDL算法的不足,提出了2点改进：一是仅利用0阶和部分1阶测试确定网络侯选连接图,在有效限制搜索空间的同时,减少了独立性测试及对数据库的扫描次数;二是利用互信息的启发性知识作为侯选父母节点排序,加大了B＆B搜索树的截断,加速了搜索过程。在通用数据集上的实验结果表明,在保证学习精度的前提下,算法整体的时间性能比原算法有较大的改进.
英文摘要：
Aiming at the hybrid algorithm I-B＆B-MDL, an improved method is proposed. Firstly, it uses order-0 and partial order-1 independence tests to obtain an original Bayesian network structure. This reduces the number of independence tests and database passes while effectively restricting the search space. Secondly, it takes mutual information between nodes as heuristic knowledge perform sort order for candidate parent nodes, which increases the cut-offs of B＆B search trees and accelerates the search process. The experimental results on the currency database show that the modified algorithm is quicker than .some hybrid algorithms while keeping a high accuracy, and it can handle large data sets.
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