Clustering on ionosphere
24.81Adjusted Rand Index (ARI)GTSA-PCA-W
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| GTSA-PCA-WClustering Algorithm=HDBSCAN, Embedding Dimension=22026.04 | 24.81 | 57.48 | 24.96 | |
| UMAPClustering Algorithm=HDBSCAN, Embedding Dimension=22026.04 | 16.55 | 50.25 | 22.78 | |
| GTSA-PCA-WClustering Method=Agglomerative, Dimensionality=2D, Distance Metric=Wasserstein2026.04 | 15.89 | 59.21 | 13.01 | |
| Kernel PCA (RBF)Dimensionality Reduction Method=Kernel PCA (RBF), Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 14.52 | 59.5 | 18.57 | |
| Regular PCADimensionality Reduction Method=Regular PCA, Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 5.45 | 67.81 | 3 | |
| GTSA-PCADimensionality Reduction Method=GTSA-PCA, Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 2.32 | 59.3 | 21.44 | |
| UMAPClustering Method=Agglomerative, Dimensionality=2D2026.04 | 0.38 | 54.31 | 3.92 |