Computer Science ›› 2015, Vol. 42 ›› Issue (6): 262-267.doi: 10.11896/j.issn.1002-137X.2015.06.055

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Accelerated Structure Learning for General Multi-dimensional Bayesian Network Classifier

FU Shun-kai and LI Zhi-qiang Sein Minn   

  • Online:2018-11-14 Published:2018-11-14

Abstract: General multi-dimensional Bayesian network classifier (GMBNC) is one kind of Bayesian network (BN) tailored for the application of multi-dimensional classification,hence it contains only features necessary for the prediction.To avoid global search,a novel algorithm called DOS-GMBNC was proposed.It inherits the framework of existing IPC-GMBNC,conducts a dynamic order of search by making use of the underlying topology information.Experimental stu-dies indicate the effectiveness and efficiency of DOS-GMBNC.It outputs networks with equal quality as PC and iPC-GMBNC algorithms,and it brings considerable reduction of computation complexity,e.g.about 89% and 45% less than PC and IPC-GMBNC respectively on a 100-node network problem.

Key words: Multi-dimensional classification,Bayesian network,Multi-dimensional Bayesian network classifier,Markov blanket

[1] 任佳,杜文才,白勇.基于贝叶斯网络自适应推理的无人机任务决策[J].系统工程理论与实践,2013,3(10):2575-2582 Ren Jia,Du Wen-cai,Bai Yong.UAV mission decision-making based on Bayesian networks adaptive inference [J].Systems Engineering-Theory & Practice,2013,3(10):2575-2582
[2] 梁洁,蔡琦,初珠立,等.反应堆补水系统诊断贝叶斯网络的建立和应用[J].原子能科学技术,2013,7(10):1840-1844 Liang Jie,Cai Qi,Chu Zhu-li,et al.Constitution and application of reactor make-up system’s fault diagnostic Bayesian networks [J].Atomic Energy Science and Technology,2013,7(10):1840-1844
[3] 刘建伟,黎海恩,罗雄麟.概率图模型学习技术研究进展[J].自动化学报,2014,0(6):1025-1044 Liu Jian-wei,Li Hai-en,Luo Xiong-lin.Learning technique of probabilistic graphical models:a review [J].ACTA Automatica Sinica,2014,0(6):1025-1044
[4] Chickering D M,Geiger D,Heckerman D.Learning BayesianNetwork is NP-Hard[R].Microsoft,1994
[5] Zhang H,Liang Liang-xiao,Su Jiang.Hidden Nave Bayes[C]∥Proceedings of Canadian Artificial Intelligence Conference.2005:432-441
[6] Bielza C,Larranaga P.Discrete Bayesian Network Classifiers:A Survey[J].ACM Computing Surveys,2014,7(1)
[7] Friedman N,Gierger D,Goldszmidt M.Bayesian Network Classifiers [J].Machine Learning,1997,29:131-163
[8] van der Gaag L C,de Waal P R.Multi-dimensional BayesianNetwork Classifiers [C]∥Proceedings of 3rd European Workshop on Probabilistic Graphical Models (PGM).2006
[9] de Waal P R,van der Gaag L C.Inference and learning in multi-dimensional Bayesian network classifiers [C]∥Proceedings of 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU).2007:501-511
[10] Zaragoza J C,Sucar E,Morales E.A Two-step Method to Learn Multi-dimensional Bayesian Network Classifiers based on MutualInformation Measures [C]∥Proceedings of 24th International FLAIRS Conference.2011
[11] Borchani H,Bielza C,Martinez-Martin P,et al.Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers:An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Di-sease Questionnaire (PDQ-39) [J].Journal of Biomedical Informatics,2012,5(6):1175-1184
[12] Zaragoza J C,Sucar E,Morales E,et al.Bayesian chain classifiers for multidimensional classification [C]∥Proceedings of 22nd International Joint Conference on Artificial Intelligence(IJ-CAI).2011:2092-2097
[13] Zhang Min-ling,Zhou Zhi-hua.A Lazy Learning Approach toMulti-label Learning [J].Pattern Recognition,2007,40(7):2038-2048
[14] 傅顺开,Minn S,李志强.多维贝叶斯网络分类器结构学习算法[J].计算机应用,2014,4(4):1083-1088 Fu Shun-kai,Minn S,Li Zhi-qiang.Structure learning algorithm for general multi-dimensional Bayesian network classifiers[J].Journal of Computer Application,2014,4(4):1083-1088
[15] Spirtes P,Glymour C,Scheines R.Causation,Prediction,andSearch(Second Edition)[M].The MIT Press,2001
[16] Bromberg F,Margaritis D,Honavar V.Efficient Markov network structure discovery using independence tests[J].Journal of Artificial Intelligence,2009,35(1):449-484
[17] Zhang Min-ling,Zhou Zhi-hua.Multi-label neural networks with applications to functional genomics and text categorization [J].IEEE Transactions on Knowledge and Data Engineering,2006,8(10):1338-1351
[18] Borchani H,Bielza C,Toro C,et al.Predicting human immuno-deficiency virus inhibitors using multi-dimensional Bayesian network classifiers [J].Artificial Intelligence in Medicine,2013,57(3):219-229

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