计算机科学 ›› 2015, Vol. 42 ›› Issue (3): 214-217.doi: 10.11896/j.issn.1002-137X.2015.03.044
魏中强,徐宏喆,李 文,桂小林
WEI Zhong-qiang, XU Hong-zhe, LI Wen and GUI Xiao-lin
摘要： 贝叶斯网络分类器的精确构造是NP难问题,使用K2算法可以有效地缩减搜索空间,提高学习效率。然而K2算法需要初始的节点次序作为输入,这在缺少先验信息的情况下很难确定；另一方面,K2算法采用贪婪的搜索策略,容易陷入局部最优解。提出了一种基于条件互信息和概率突跳机制的贝叶斯网络结构学习算法(CMI-PK2算法),该算法首先利用条件互信息生成有效的节点次序作为K2算法的输入,然后利用概率突跳机制改进K2算法的搜索过程来提高算法的全局寻优能力,学习较为理想的网络结构。在两个基准网络Asia和Alarm上进行了实验验证,结果表明CMI-PK2算法具有更高的分类精度和数据拟合程度。
| [1] Pearl J.Fusion,Propagation,and Structuring in Belief Networks[J].Artificial Intelligence,1986,29:241-288 [2] 黄建明.贝叶斯网络在学生成绩预测中的应用[J].计算机科学,2012,9(11A):280-282 [3] 李亚飞,吕强,苏伟峰,等.一种小规模数据集下的贝叶斯网络学习方法及其应用[J].计算机科学,2011,8(7):181-184 [4] Wong M L,Leung K S.An efficient data mining method forlearning Bayesian networks using an evolutionary algorithm based hybrid approach[J].IEEE Transactions on Evolutionary Computation,2004,8(4):378-404 [5] Chen X W.Improving Bayesian Network structure learning with mutual information-based node ordering in the K2 algorithm[J].IEEE Transactions on Knowledge and Data Engineering,2008,20(1):1-13 [6] 冀俊忠,张鸿勋,胡仁兵,等.基于独立性测试和蚁群优化的贝叶斯网结构学习算法[J].自动化学报,2009,35(3):281-288 [7] Darwiche A.A differential approach to inference in Bayesiannetworks[J].Journal of ACM,2003,0(3):280-305 [8] Lerner B,Malka R.Investigation of the K2 algorithm in learning Bayesian network classifiers[J].Applied Artificial Intelligence,2011,25(1):74-96 [9] Cooper G F,Herskovits E.A Bayesian method for the induction of probabilistic networks from data[J].Machine Learning,1992,9(4):309-347 [10] Chen X W,Anantha G,Lin X.Improving Bayesian networkstructure learning with mutual information-based node ordering in the K2 algorithm[J].IEEE Transactions on Knowledge and Data Engineering,2008,20(5):628-640 [11] Zhang Y,Zhang W,Xie Y.Improved heuristic equivalent search algorithm based on Maximal Information Coefficient for Baye-sian Network Structure Learning[J].Neurocomputing,2013,117(2):186-195 [12] Chickering D M.Optimal structure identification with greedysearch[J].The Journal of Machine Learning Researeh,2002,3 :507-554 [13] Fleuret F.Fast binary feature selection with conditional mutual information[J].The Journal of Machine Learning Research,2004,5:1531-1555 [14] Al-Rifaie M M,Blackwell T.Bare bones particle swarms with jumps[M].Swarm Intelligence.Springer Berlin Heidelberg,2012:49-60 [15] Jiang J,Wang J,Yu H,et al.Poison Identification Based onBayesian Network:A Novel Improvement on K2 Algorithm via Markov Blanket[M].Advances in Swarm Intelligence.Springer Berlin Heidelberg,2013:173-182 [16] Lauritzen S L,Spiegelhalter D J.Local computations with probabilities on graphical structures and their application to expert systems[J].Journal of the Royal Statistical Society,Series B (Methodological),1988,50(2):157-224 [17] Beinlich I A,Suermondt H J,Chavez R M,et al.The ALARM monitoring system[C]∥A case study with two probabilistic inference techniques for belief networks.Springer Berlin Heidelberg,1989:247-256 |
| No related articles found! |
|
||
首页