论文标题
关于非二元定性概率网络中错误推断的注释
A note on incorrect inferences in non-binary qualitative probabilistic networks
论文作者
论文摘要
定性概率网络（QPN）将贝叶斯网络的条件独立性假设与正相关的定性特性结合在一起。他们正式化了积极依赖性的各种直观属性，以允许对大型变量网络进行推断。但是，我们将在本文中证明，由于不正确的对称属性，在非二元QPN中获得的许多推论在数学上不是正确的。我们将提供这种不正确推论的示例，并简要讨论可能的决议。
Qualitative probabilistic networks (QPNs) combine the conditional independence assumptions of Bayesian networks with the qualitative properties of positive and negative dependence. They formalise various intuitive properties of positive dependence to allow inferences over a large network of variables. However, we will demonstrate in this paper that, due to an incorrect symmetry property, many inferences obtained in non-binary QPNs are not mathematically true. We will provide examples of such incorrect inferences and briefly discuss possible resolutions.
