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

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