Abstract
We show that a conditional probability table (CPT) is obtained after every multiplication and every marginalization step when eliminating variables from a discrete Bayesian network. The main advantage of our work is an improvement in presentation. The probability distributions constructed during variable elimination in Bayesian networks have always been denoted as potentials. Since CPTs are a special case of potential, our description is more precise and readable.
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Butz, C.J., Yan, W., Lingras, P., Yao, Y.Y. (2010). The CPT Structure of Variable Elimination in Discrete Bayesian Networks. In: Ras, Z.W., Tsay, LS. (eds) Advances in Intelligent Information Systems. Studies in Computational Intelligence, vol 265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05183-8_10
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DOI: https://doi.org/10.1007/978-3-642-05183-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05182-1
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