Portraying probabilistic relationships of continuous nodes in Bayesian networks with ranked nodes method
نویسندگان
چکیده
This paper advances the use of ranked nodes method (RNM) to portray probabilistic relationships continuous quantities in Bayesian networks (BNs). In RNM, are represented by with discrete ordinal scales. The quantified conditional probability tables (CPTs) generated expert-elicited parameters. When formed discretizing scales, ignorance about functioning RNM can lead discretizations that make generation sensible CPTs impossible. While a guideline exists on this matter, it is limited requirement define an equal number states for all nodes. presents two novel discretization approaches consider and allow have non-equal numbers states. first one, called “static approach”, be given any desired stay unchanged during BN. second “dynamic algorithmically updated BN help manage sizes CPTs. Both based original idea that, besides parameters, relationship defined initial RNM-compatible elicited from domain expert. Overall, new offer easier more versatile way using depict quantities. doing so, they also facilitate effective diverse BNs decision support systems.
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ژورنال
عنوان ژورنال: Decision Support Systems
سال: 2022
ISSN: ['1873-5797', '0167-9236']
DOI: https://doi.org/10.1016/j.dss.2021.113709