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. © 2010 Springer-Verlag.
Cite
CITATION STYLE
Śniezyński, B., Łukasik, T., & Mierzwa, M. (2010). B2R: An algorithm for converting Bayesian networks to sets of rules. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6262 LNCS, pp. 177–184). https://doi.org/10.1007/978-3-642-15251-1_14
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