Optimizing the induction of Bayesian Networks using PC and Variable Ordering Genetic Algorithms

Abstract

Variable Ordering (VO) plays an important role when inducing Bayesian Networks (BN). Previous works in the literature suggest that it is worth pursuing the use of genetic algorithms for identifying a suitable VO, when learning a BN structure from data. However, these algorithms may be computationally costly. This paper proposes a hybrid adaptive algorithm… (More)

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