Modeling patterns of evidence in Bayesian networks: a case-study in Classical Swine Fever

L.C. van der Gaag, J. Bolt, W.L.A. Loeffen, A.R.W. Elbers

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

10 Citations (Scopus)

Abstract

Upon engineering a Bayesian network for the early detection of Classical Swine Fever in pigs, we found that the commonly used approach of separately modelling the relevant observable variables would not suffice to arrive at satisfactory performance of the network: explicit modelling of combinations of observations was required to allow identifying and reasoning about patterns of evidence. In this paper, we outline a general approach to modelling relevant patterns of evidence in a Bayesian network. We demonstrate its application for our problem domain and show that it served to significantly improve our network’s performance.
Original languageEnglish
Title of host publication Computational Intelligence for Knowledge-Based System Design
EditorsE. Hüllermeier, R. Kruse, F. Hoffmann
Place of PublicationDortmund
PublisherSpringer
Pages675-684
Number of pages9
ISBN (Electronic)9783642140495
ISBN (Print)9783642140488
DOIs
Publication statusPublished - Jun 2010
Event13th IPMU Conference - Dortmund, Germany
Duration: 28 Jun 20102 Jul 2010

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume6178
ISSN (Print)0302-9743

Conference

Conference13th IPMU Conference
Country/TerritoryGermany
CityDortmund
Period28/06/102/07/10

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