Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved
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- 作者：Anthony Costa Constantinoua ; anthony@constantinou.info" class="auth_mail" title="E-mail the corresponding author ; Norman Fentona ; b ; n.fenton@qmul.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Martin Neila ; b ; m.neil@qmul.ac.uk" class="auth_mail" title="E-mail the corresponding author
- 关键词：Bayesian networks ; Belief networks ; Causal inference ; Expert knowledge ; Knowledge elicitation ; Probabilistic graphical models
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：1 September 2016
- 年：2016
- 卷：56
- 期：Complete
- 页码：197-208
- 全文大小：2234 K
文摘
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A method for integrating expert knowledge with data in Bayesian networks.
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Preserves the data-driven expectations when the expert variables remain unobserved.
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Supports the incorporation of extremely rare or previously unobserved events.
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The method extends towards determining the accuracy of expertise.