Learning Bayesian Networks with R
作者： Claus Dethlefsen , Susanne G. Bøttcher
DOI:
关键词: Artificial intelligence 、 Variable-order Bayesian network 、 Prior probability 、 Gaussian 、 Bayesian network 、 Machine learning 、 Interface (computing) 、 Structure (mathematical logic) 、 Basis (linear algebra) 、 Metric (mathematics) 、 Computer science
摘要: deal i s a software package freely available for use with R. It includes several methods analysing data using Bayesian networks variables of discrete and/or continuous types but restricted to conditionally Gaussian networks. Construction priors network parameters is supported and their can be learned from conjugate updating. The score used as metric learn the structure forms basis heuristic search strategy. has an interface Hugin.
参考文章(10)
Robert G. Cowell, V. Nair, David J. Spiegelhalter, Steffen L. Lauritzen, A. Philip David, M. Jordan, J. Lawless, Probabilistic Networks and Expert Systems In: UNSPECIFIED Springer-Verlag (1999). ,(1999)
Peter J Green, Nils Lid Hjort, Sylvia Richardson, Highly Structured Stochastic Systems ,(2003)
Steffen Lilholt Lauritzen, Some modern applications of graphical models Oxford University Press. ,(2003)
Susanne Gammelgaard Bøttcher, Learning Bayesian Networks with Mixed Variables international conference on artificial intelligence and statistics. ,(2001)
Ross Ihaka, Robert Gentleman, R: A Language for Data Analysis and Graphics Journal of Computational and Graphical Statistics. ,vol. 5, pp. 299- 314 ,(1996) , 10.1080/10618600.1996.10474713
Ross D. Shachter, C. Robert Kenley, Gaussian influence diagrams Management Science. ,vol. 35, pp. 527- 550 ,(1989) , 10.1287/MNSC.35.5.527
Steffen L. Lauritzen, Propagation of Probabilities, Means, and Variances in Mixed Graphical Association Models Journal of the American Statistical Association. ,vol. 87, pp. 1098- 1108 ,(1992) , 10.1080/01621459.1992.10476265
Optimal structure identification with greedy search Journal of Machine Learning Research. ,vol. 3, pp. 507- 554 ,(2003) , 10.1162/153244303321897717
Dan Geiger, David Heckerman, Learning Gaussian Networks Uncertainty Proceedings 1994. pp. 235- 243 ,(1994) , 10.1016/B978-1-55860-332-5.50035-3
David Heckerman, Dan Geiger, David M. Chickering, Learning Bayesian Networks: The Combination of Knowledge and Statistical Data Machine Learning. ,vol. 20, pp. 197- 243 ,(1995) , 10.1023/A:1022623210503