Application of Bayesian Network Learning Methods to Waste Water Treatment Plants
Applied Intelligence
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
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In this paper we show how a user can influence recovery of Bayesian Networks from a database by specifying prior knowledge. The main novelty of our approach is that the user only has to provide partial prior knowledge, which is then completed to a full prior over all possible network structures. This partial prior knowledge is expressed among variables in an intuitive pairwise way, which embodies the uncertainty of the user about his/her own prior knowledge. Thus, the uncertainty of the model is updated in the normal Bayesian way.