Fig. 1.

Consensus clustering yields K = 8 as an optimal number of clusters. (A) Clustering quality (1 minus the percentage of ambiguously clustered frames, or PAC) across candidate cluster numbers. The color gradient for a given cluster number denotes the assessment of clustering quality with a more or less strict definition of “ambiguous clustering” (darker shades denote a more lenient one). Quality gradually increases until it reaches a plateau for large numbers of clusters. (B) When fitting an exponential function to the data and subtracting it from the actual clustering quality values, the positive-valued peaks denote cluster numbers for which the rise in quality measure exceeds that expected from the trend alone (see Bolton et al., 2020b). K_opt = 8 was selected for further analyses, as it was the global optimum within the investigated range.