Functional group classification using consensus clustering
Fig 2
Optimization for number of groups.
All BIC curves and the resulting average curve, shown for a) unscaled and b) scaled data. c): Silhouette score for different aggregations of the consensus matrix. A higher value of K means going lower in the dendrogram, hence splitting one group. Note that BIC is optimized independently for each resample in (a) and (b), and therefore partitions with the same number of clusters may differ substantially. In contrast, the Silhouette score is optimized at the aggregated level across all resamples. As a result, the optimal number of clusters identified by these two criteria will not necessarily coincide.