Fig. 3: Communities detected in a Workplace dataset from partial observations of close-proximity interactions.
From: Structure and inference in hypergraphs with node attributes
We vary the fraction of hyperedges given in input to the algorithms (top: 100%, bottom: 50%) and compare the inferred communities against the attribute departement (top left). The AUC barplot (bottom-left) shows the performance of the models in hyperedge prediction. Bars and error bars are averages and standard deviations over 5 cross-validation folds. This plot shows that HyCoSBM is able to use the attributes effectively to keep performance high even at a low fraction of input observations.
