A Bayesian method for learning belief networks that contain hidden variables-Reference-Cited by-同舟云学术

A Bayesian method for learning belief networks that contain hidden variables

Published:1995-01 Issue:1 Volume:4 Page:71-88
ISSN:0925-9902
Container-title:Journal of Intelligent Information Systems
language:en
Short-container-title:J Intell Inf Syst

Author:

Cooper Gregory F.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Link

http://link.springer.com/content/pdf/10.1007/BF00962823.pdf

Reference27 articles.

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3. Beinlich, I.A., Suermondt, H.J., Chavez, R.M. and Cooper, G.F. (1989). ?The ALARM monitoring system: A case study with two probabilistic inference techniques for belief networks,? inProceedings of the Second European Conference on Artificial Intelligence in Medicine, London, England, pp. 247?256.

4. Chavez, R.M. and Cooper, G.F. (1990). KNET: Integrating hypermedia and normative Bayesian modeling. In: Shachter, R.D., Levitt, T.S., Kanal, L.N. and Lemmer, J.F. (Eds.),Uncertainty in Artificial Intelligence 4. North-Holland, Amsterdam, pp. 339?349.

5. Cheeseman, P., Self, M., Kelly, J., Taylor, W., Freeman, D. and Stutz, J. (1988). ?Bayesian classification,? inProceedings of AAAI, St. Paul, MN, pp. 607?611.

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