Clustering on heart-h
0.3168ARIGTSA-PCA-W
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| GTSA-PCA-WClustering Method=Agglomerative, Dimensionality=2D, Distance Metric=Wasserstein2026.04 | 0.3168 | 0.6799 | 0.2231 | |
| GTSA-PCA-WClustering Algorithm=HDBSCAN, Embedding Dimension=22026.04 | 0.3066 | 0.6672 | 0.2021 | |
| GTSA-PCAFeature Space=Two-dimensional, Clustering Algorithm=HDBSCAN2026.04 | 0.3065 | 0.662 | 0.2074 | |
| UMAPClustering Method=Agglomerative, Dimensionality=2D2026.04 | 0.2783 | 0.6653 | 0.1901 | |
| UMAPClustering Algorithm=HDBSCAN, Embedding Dimension=22026.04 | 0.1496 | 0.528 | 0.2093 | |
| Regular PCAFeature Space=Two-dimensional, Clustering Algorithm=HDBSCAN2026.04 | 0.1466 | 0.5244 | 0.1287 | |
| Kernel PCA (RBF)Feature Space=Two-dimensional, Clustering Algorithm=HDBSCAN2026.04 | -0.0028 | 0.4295 | 0.0515 |