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* вычисление наиболее вероятного объяснения наблюдаемого события, | * вычисление наиболее вероятного объяснения наблюдаемого события, | ||
* вычисление апостериорного максимума. | * вычисление апостериорного максимума. | ||
==Литература== | |||
* Jensen Finn V. Bayesian Networks and Decision Graphs. — Springer, 2001. | |||
* Judea Pearl, Stuart Russell. Bayesian Networks. UCLA Cognitive Systems Laboratory, Technical Report (R-277), November 2000. | |||
* Judea Pearl, Stuart Russell. Bayesian Networks, in M. A. Arbib (Ed.), Handbook of Brain Theory and Neural Networks, pp. 157—160, Cambridge, MA: MIT Press, 2003, ISBN 0-262-01197-2. | |||
* Neil M, Fenton N, Tailor M, «Using Bayesian Networks to model Expected and Unexpected Operational Losses», Risk Analysis: An International Journal, Vol 25(4), 963—972, 2005. http://www.dcs.qmul.ac.uk/~norman/papers/oprisk.pdf | |||
* Enrique Castillo, José Manuel Gutiérrez, and Ali S. Hadi. Expert Systems and Probabilistic Network Models. New York: Springer-Verlag, 1997. ISBN 0-387-94858-9 | |||
* Fenton NE and Neil M, «Combining evidence in risk analysis using Bayesian Networks». https://www.dcs.qmul.ac.uk/~norman/papers/Combining%20evidence%20in%20risk%20analysis%20using%20BNs.pdf | |||
* Judea Pearl. Fusion, propagation, and structuring in belief networks. Artificial Intelligence 29(3):241—288, 1986. | |||
* Pearl Judea. Probabilistic Reasoning in Intelligent Systems. — Morgan Kaufmann, 1988. — ISBN 0-934613-73-7.Judea Pearl. Causality. 2000. | |||
* J.W. Comley and D.L. Dowe, «Minimum Message Length, MDL and Generalised Bayesian Networks with Asymmetric Languages», chapter 11 (pp265—294) in P. Grunwald, M.A. Pitt and I.J. Myung (eds)., Advances in Minimum Description Length: Theory and Applications, Cambridge, MA: MIT Press, April 2005, ISBN 0-262-07262-9. (This paper puts decision trees in internal nodes of Bayes networks using Minimum Message Length (MML). An earlier version is Comley and Dowe (2003), .pdf.) | |||
* Christian Borgelt and Rudolf Kruse. Graphical Models — Methods for Data Analysis and Mining, Chichester, UK: Wiley, 2002, ISBN 0-470-84337-3 | |||
* Korb Kevin B. Bayesian Artificial Intelligence. — CRC Press, 2004. — ISBN 1-58488-387-1. | |||
* Nevin Lianwen Zhang and David Poole, A simple approach to Bayesian network computations, Proceedings of the Tenth Biennial Canadian Artificial Intelligence Conference (AI-94), Banff, May 1994, 171—178. This paper presents variable elimination for belief networks. | |||
* David Heckerman, A Tutorial on Learning with Bayesian Networks. In Learning in Graphical Models, M. Jordan, ed. MIT Press, Cambridge, MA, 1999. Also appears as Technical Report MSR-TR-95-06, Microsoft Research, March, 1995. An earlier version appears as Bayesian Networks for Data Mining, Data Mining and Knowledge Discovery, 1:79-119, 1997. The paper is about both parameter and structure learning in Bayesian networks. | |||
