Modelling patterns of evidence in Bayesian networks: a case-study in classical swine fever

Authors:
Linda C. Van Der Gaag;Janneke Bolt;Willie Loeffen;Armin Elbers
Affiliations:
Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands;Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands;Central Veterinary Institute, Wageningen UR, Lelystad, The Netherlands;Central Veterinary Institute, Wageningen UR, Lelystad, The Netherlands
Venue:
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Year:
2010

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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.