Alternative Initial Probability Tables for Elicitation of Bayesian Belief Networks

F. Phillipson; P. Langenkamp; R. Wolthuis

doi:10.3390/mca26030054

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 journal › Article › Academic › peer-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 language	English
Article number	54
Number of pages	10
Journal	Mathematical and Computational Applications
Volume	26
Issue number	3
DOIs	https://doi.org/10.3390/mca26030054
Publication status	Published - 1 Sept 2021

Keywords

Bayesian Belief Networks
expert elicitation
conditional probability

Access to Document

10.3390/mca26030054Licence: CC BY

Cite this

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