Multi-dataset performance of “Learn & Vote” versus six other methods.

Each row corresponds to a specific dataset derived from a specific underlying ground-truth network (as described in detail in Methods and Datasets). Each row is split into three structure learning performance metrics (precision, recall, and “F1” score, harmonic mean of precision and recall). For each sub-row, the highest performance measurement is boldfaced. Each column corresponds to a specific method for causal network inference (as described in detail in Methods and Datasets), with the performance measures of our method (“Learn and Vote”) in the rightmost column. The symbol “n/a” denotes that no performance results were available for that method on that dataset. Here, the method “simy” is only feasible for networks containing up to 20 nodes, so it failed to produce results on the larger networks. The network size denotes the number of nodes in the indicated network. The network type is as follows: RW, real-world; S, synthetic.