Sensitivity analysis for threshold decision making with Bayesian belief networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1792, Issue , 2000, Pages 37-48

  van der Gaag, Linda C ^a   Coupé, Veerle M H ^b  

^a UTRECHT UNIVERSITY   (Netherlands)

^b ERASMUS UNIVERSITY ROTTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION MAKING; DECISION THEORY; SENSITIVITY ANALYSIS;

INTEGRAL PART; NETWORK INFLUENCES; PROBABILITY ASSESSMENTS; THRESHOLD MODEL;

BAYESIAN NETWORKS;

EID: 34250370639     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (8)

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2. V.M.H. Coupé, L.C. van der Gaag (1998). Practicable sensitivity analysis of Bayesian belief networks. In: M. Hušková, P. Lachout, J.A. Víšek (Editors). Prague Stochastics ’98, Union of Czech Mathematicians and Physicists, Prague, pp. 81–86; also available as Report UU-CS-1998-10, Utrecht University.
3. M.J. Druzdzel, L.C. van der Gaag (1995). Elicitation of probabilities for belief networks: combining qualitative and quantitative information. In: P. Besnard, S. Hanks (Editors). Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann, Palo Alto, pp. 141–148.
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7. S.G. Pauker, J.P. Kassirer (1980). The threshold approach to clinical decision making. New England Journal of Medicine, vol. 302, pp. 1109–1117.
8. D. Kahneman, P. Slovic, A. Tversky (1982). Judgement under Uncertainty: Heuristics and Biases, Cambridge University Press, Cambridge.