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Using the Noisy-OR Model Can Be Harmful... But It Often Is Not

机译:使用嘈杂或模型可能有害......但它往往不是

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摘要

The noisy-OR model and its generalizations are frequently used for alleviating the burden of probability elicitation upon building Bayesian networks with the help of domain experts. The results from empirical studies consistently suggest that, when compared with a fully expert-quantified network, using the noisy-OR model will just have a minor effect on the performance of a network. In this paper, we address this apparent robustness and investigate its origin. Our results show that ill-considered use of the noisy-OR model can substantially decrease a network's performance, yet also that the model has broader applicability than it was originally designed for.
机译:嘈杂或模型及其概括经常用于减轻在领域专家的帮助下建立贝叶斯网络时概率诱因的负担。实证研究的结果一直表明,与完全专业的网络相比,使用嘈杂或模型将对网络性能进行轻微影响。在本文中,我们解决了这种明显的鲁棒性并调查了它的起源。我们的结果表明,考虑了嘈杂的或模型的使用可能大大降低了网络的性能,而且该模型的适用性也比最初为设计。

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