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• W335904211 abstract "We propose a novel algorithm for extracting the structure of a Bayesian network from a dataset. Our approach is based on generalized conditional entropies, a parametric family of entropies that extends the usual Shannon conditional entropy. Our results indicate that with an appropriate choice of a generalized conditional entropy we obtain Bayesian networks that have superior scores compared to similar structures obtained by classical inference methods." @default.
• W335904211 created "2016-06-24" @default.
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• W335904211 date "2008-01-01" @default.
• W335904211 modified "2023-09-26" @default.
• W335904211 title "Structure Inference of Bayesian Networks from Data: A New Approach Based on Generalized Conditional Entropy." @default.
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