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Volumn 12, Issue 4, 2000, Pages 499-508

Dealing with the expert inconsistency in probability elicitation

Author keywords

Analytic hierarchy process; Bayesian belief networks; Probability elicitation

Indexed keywords

ADAPTIVE SYSTEMS; APPROXIMATION THEORY; EXPERT SYSTEMS; MEDICAL APPLICATIONS; NEURAL NETWORKS; PROBABILITY; SENSITIVITY ANALYSIS; SYSTEMS ANALYSIS;

EID: 0034215459     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/69.868903     Document Type: Article
Times cited : (52)

References (20)
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  • 8
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  • 9
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    • Learning Bayesian Belief Networks - An Approach Based on the MDL Principle
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    • Lam, W.1    Bacchus, F.2
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    • Also in Readings in Medical Artificial Intelligence: The First Decade, W.J. Clancey and E.H. Shortliffe, eds. Reading, Massachusetts: Addison-Wesley, pp. 190-209.
    • Readings in Medical Artificial Intelligence: The First Decade , pp. 190-209
  • 12
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    • The Sensitivity of Belief Networks to Imprecise Probabilities: An Experimental Investigation
    • M. Pradhan, M. Henrion, G. Provan, B. Del Favero, and K. Huang, "The Sensitivity of Belief Networks to Imprecise Probabilities: An Experimental Investigation," Artificial Intelligence, vol. 85, no. 1-2, pp. 363-397, 1996.
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  • 19
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    • Assessment, Criticism, and Improvement of Imprecise Subjective Probabilities for a Medical Expert System
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.