论文标题
网络特征对网络重建的影响
Impact of network characteristics on network reconstruction
论文作者
论文摘要
当从数据中推断网络时，可能会出现两种类型的错误：关于链接的存在的假阳性和假阴性结论。在耦合振荡器网络的情况下，我们关注局部网络特征对I型假阳性结论的概率$α$的影响，以及II型假阴性结论的概率$β$。我们证明，错误的结论概率受到局部连通性测量的影响，例如最短路径长度和弯曲程度，当不知道真正的基础网络时，这也可以从推断网络中估算出来。然后，这些措施可用于量化链接结论的置信度，并通过链接阈值的高级概念来改善网络重建。
When a network is inferred from data, two types of errors can occur: false positive and false negative conclusions about the presence of links. We focus on the influence of local network characteristics on the probability $α$ - of type I false positive conclusions, and on the probability $β$ - of type II false negative conclusions, in the case of networks of coupled oscillators. We demonstrate that false conclusion probabilities are influenced by local connectivity measures such as the shortest path length and the detour degree, which can also be estimated from the inferred network when the true underlying network is not known a priory. These measures can then be used for quantification of the confidence level of link conclusions, and for improving the network reconstruction via advanced concepts of link thresholding.
