Abstract
In this paper B2R algorithm that converts Bayesian networks into sets of rules is proposed. It is tested on several data sets with various configurations and results show that accuracy is similar to original Bayesian networks even after pruning a high number of rules. It allows to exploit advantages of both knowledge representation techniques.
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Śnieżyński, B., Łukasik, T., Mierzwa, M. (2010). B2R: An Algorithm for Converting Bayesian Networks to Sets of Rules. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15251-1_14
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DOI: https://doi.org/10.1007/978-3-642-15251-1_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15250-4
Online ISBN: 978-3-642-15251-1
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