Fig. 8
From: Probabilistic network sparsification with ego betweenness
Required number of samples to calculate measures over sparsified graphs with errors lower than a specific threshold: a–c The original graph is Erdős–Rényi with \(\rho = 0.1\). The sparsification ratio is \(\alpha = 0.45\) and backboning method the maximum spanning tree method, d–f the original graph is the brain network, sparsification ratio is \(\alpha = 0.55\) and the backboning method is the noise corrected method