Abstract:The objective of Smart Manufacturing is to improve productivity and competitiveness in industry, based on in-process data. It requires reliable, explainable and understandable models such as Bayesian networks for performing tasks like condition prediction. In this context, a Bayesian network can be classically learned in a supervised, unsupervised way or a semi-supervised way. Here, we are interested in how to perform the learning when the ground truth isn't included in the learning data but is observable indi… Show more
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