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贝叶斯网络模型概述 被引量:12

Summary of Bayesian Network
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摘要 文章对贝叶斯网络分类模型进行了形式化的描述,重点介绍了构造贝叶斯网的三种不同的方式,最后总结了贝叶斯网络的优点。 In the paper, we suggest a data model formalizes of Bayesian network, sum up three construct methods for the Bayesian network. At last, the authors give some advantages of Bayesian network in the end.
出处 《电脑与信息技术》 2008年第5期41-42,共2页 Computer and Information Technology
基金 河南科技大学教改项目(G2003-21) 河南科技大学实验技术开发基金项目(SY0304016)
关键词 数据挖掘 贝叶斯网络 贝叶斯网络分类模型 data mining Bayesian network Bayesian classifier
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  • 1[1]Heckerman D. Bayesian networks for data mining [J]. Data Mining and Knowledge Discovery, 1997, 1: 79~119.
  • 2[2]Heckerman D, Geiger D, Chickering D. Learning Bayesian Networks: the combination of knowledge and statistical data [J]. Machine Learning, 1995, 20: 196~243.
  • 3[3]Geiger D, Heckerman D. A characterization of the Dirichlet distribution with applicable to learning Bayesian networks [A]. In Proceedings of Eleventh Conference on Uncertainty in Artificial Intelligence [C]. Montreal, QU, 1995. 196~207.
  • 4[4]Cooper G, Herskovits E. A Bayesian method for the induction of probabilistic networks from data [J]. Machine Learning, 1992, 9: 309~347.
  • 5[5]Dagum P, Luby M. Approximating probabilistic inference in Bayesian belief networks is NP-hard [J]. Artificial Intelligence, 1993, 60: 141~153.
  • 6[6]Chickering D. Learning equivalence classes of Bayesian-network structures [A]. In Proceedings of Twelfth Conference on Uncertainty in Artificial Intelligence [C]. Portland, OR: Morgan Kaufmann, 1996.
  • 7[7]Heckerman D, Mamdani A, Wellman M. Real-world applications of Bayesian networks [J]. Communications of the ACM, 1995, 38 (3): 24~26.
  • 8[8]Sewell W, Shah V. Social class, parental encouragement, and educational aspirations [J]. American Journal of Sociology, 1968, 73: 559~572.
  • 9[9]Spirtes P, Glymour C, Scheines R. Causation, Predication, and Search [M]. New York: Springer-Verlag, 1993.
  • 10[10]Cheeseman P, Stutz J. Bayesian classification (AutoClass): Theory and results [A]. Fayyad U, Piatesky-Shapiro G, Smyth P, et al (Eds.). Advances in Knowledge Discovery and Data Mining [C]. Menlo Park, CA: AAAI Press, 1995.

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