Fig. 1
From: Complex network effects on the robustness of graph convolutional networks
Processing chain for experiments. Each experiment takes a dataset, applies a method to split training, validation, and test data, applies an attack to a set of target nodes, then applies a classifier to the attacked dataset. We evaluate the robustness of vertex classification—-in terms of required attacker budget at a given attack success rate—across all possible combinations of dataset, selection methods, attacks, and classifier