Positive dependence in qualitative probabilistic networks
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Qualitative probabilistic networks (QPNs) combine the conditional independence assumptions of Bayesian networks with the `qualitative' properties of positive and negative dependence. They attempt to formalise various intuitive properties of positive dependence to allow inferences over a large network of variables. However, we highlight a key mistake in the QPN literature which means that most inferences made by a QPN are not mathematically true. We also discuss how to redefine a QPN in order to fix this issue.
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