Table 1.
UMAP and HDBSCAN (hyper)parameters set for each experiment.
| Experiment | UMAP | HDBSCAN | ||||||
|---|---|---|---|---|---|---|---|---|
| n_neighbors | min_dist | n_components | metric | min_cluster_size | min_samples | cluster_selection_epsilon | alpha | |
| 1 (Sect. 4) | 70 | 0. | 2 | ‘Euclidean’ | 70 | 1 | 0. | 1. |
| 2 (Sect. 5) | 70 | 0. | 2 | ‘Euclidean’ | 70 | 1 | 0. | 1. |
| 3 (Sect. 6, SRs) | 73 | 0.1 | 2 | ‘Euclidean’ | 60 | 1 | 0. | 1. |
| 4 (Sect. 6, FRs) | 72 | 0.9 | 2 | ‘Euclidean’ | 70 | 1 | 0. | 1. |
| 5 (Sect. 7) | 45 | 0. | 2 | ‘Euclidean’ | 150 | 1 | 0. | 1. |
Notes. n_neighbors: size of local neighbourhood used for manifold approximation; min_dist: minimum distance between embedded points; n_components: dimension of the space to embed into; metric: metric to use to compute distances in the high-dimensional space; min_cluster_size: minimum size of clusters; min_samples: number of samples in a neighbourhood for a point to be considered a core point; cluster_selection_epsilon: distance threshold below which clusters will be merged; alpha: distance scaling parameter.
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