Clustering on colic
8.19ARIGTSA-PCA-W
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| GTSA-PCA-WClustering Method=Agglomerative, Dimensionality=2D, Distance Metric=Wasserstein2026.04 | 8.19 | 56.26 | 0.1053 | |
| UMAPClustering Method=Agglomerative, Dimensionality=2D2026.04 | 1.31 | 56.02 | 0.0728 | |
| GTSA-PCADimensionality Reduction Method=GTSA-PCA, Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 0.2972 | 0.6843 | 0.2077 | |
| Kernel PCA (RBF)Dimensionality Reduction Method=Kernel PCA (RBF), Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 0.2244 | 0.6294 | 0.156 | |
| Regular PCADimensionality Reduction Method=Regular PCA, Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | -0.0007 | 0.676 | 0 |