Fig. 2: Predicting interactions in close-proximity datasets with partial observations.
From: Structure and inference in hypergraphs with node attributes
We show the performance of various methods in hyperedge prediction tasks, measured by AUC, as we vary the fraction of hyperedges made available to the algorithms. This plot shows that the performance of HyCoSBM remains high when fewer hyperedges are available in input, while that of the algorithms which do not use any attribute drops. Lines and shades around them are averages and standard deviations over 5 cross-validation folds.
