title: ExpertBayes: Automatically refining manually built Bayesian networks.
abstract: Bayesian network structures are usually built using only the data and starting from an empty network or from a naïve Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance models. In this work, we take Bayesian networks built by specialists and show that minor perturbations to this original network can yield better classifiers with a very small computational cost, while maintaining most of the intended meaning of the original model.
authors.affiliation: CRACS INESC TEC LA.
authors.forename: Ezilda
authors.initials: E
authors.lastname: Almeida
authors.affiliation: Department of Computer Science, University of Porto.
authors.forename: Pedro
authors.initials: P
authors.lastname: Ferreira
authors.affiliation: Instituto de Telecommunicações, IT-Porto.
authors.forename: Tiago
authors.initials: T
authors.lastname: Vinhoza
authors.affiliation: Department of Computer Science, University of Porto.
authors.forename: Inês
authors.initials: I
authors.lastname: Dutra
authors.affiliation: University of Wisconsin, Madison, USA.
authors.forename: Jingwei
authors.initials: J
authors.lastname: Li
authors.affiliation: University of Wisconsin, Madison, USA.
authors.forename: Yirong
authors.initials: Y
authors.lastname: Wu
authors.affiliation: University of Wisconsin, Madison, USA.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Burnside
keywords: advice-based systems; bayesian networks; learning bayesian network structures