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Learning Bayesian Networks with Heterogeneous Agronomic Data Sets via Mixed-Effect Models and Hierarchical Clustering
Rooted in the linear mixed-effects models framework and tailored for hierarchical data, this novel approach demonstrates enhanced BN learning.
A probabilistic network for the diagnosis of acute cardiopulmonary diseases
In this paper, the development of a probabilistic network for the diagnosis of acute cardiopulmonary diseases is presented.
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