Alternative Initial Probability Tables for Elicitation of Bayesian Belief Networks

F. Phillipson*, P. Langenkamp, R. Wolthuis

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Bayesian Belief Networks are used in many fields of application. Defining the conditional dependencies via conditional probability tables requires the elicitation of expert belief to fill these tables, which grow very large quickly. In this work, we propose two methods to prepare these tables based on a low number of input parameters using specific structures and one method to generate the table using probability tables of each relation of a child node with a certain parent. These tables can be used further as a starting point for elicitation
Original languageEnglish
Article number54
Number of pages10
JournalMathematical and Computational Applications
Volume26
Issue number3
DOIs
Publication statusPublished - 1 Sep 2021

Keywords

  • Bayesian Belief Networks
  • expert elicitation
  • conditional probability

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