Figure 2. Consensus clustering on the LFR benchmark.

The dots indicate the performance of the original method, the squares that obtained with consensus clustering. The parameters of the LFR benchmark graphs are: average degree 〈k〉 = 20, maximum degree k_max = 50, minimum community size c_min = 10, maximum community size c_max = 50, the degree exponent is τ₁ = 2, the community size exponent is τ₂ = 3. Each panel correspond to a clustering algorithm, indicated by the label. The two sets of plots correspond to networks with 1000 (a) and 5000 (b) vertices.