Clustering on cardiotocography
0.6807ARIGTSA-PCA
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| GTSA-PCAFeature Space=Two-dimensional, Clustering Algorithm=HDBSCAN2026.04 | 0.6807 | 0.7298 | 0.7464 | |
| GTSA-PCADimensionality Reduction Method=GTSA-PCA, Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 0.5778 | 0.6437 | 0.7358 | |
| Kernel PCA (RBF)Dimensionality Reduction Method=Kernel PCA (RBF), Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 0.2064 | 0.3219 | 0.4482 | |
| Regular PCADimensionality Reduction Method=Regular PCA, Projection Dimension=2D, Clustering Algorithm=Agglomerative Clustering, Linkage=Ward2026.04 | 0.1503 | 0.3022 | 0.3349 | |
| Kernel PCA (RBF)Feature Space=Two-dimensional, Clustering Algorithm=HDBSCAN2026.04 | 0.0511 | 0.397 | 0.1977 | |
| Regular PCAFeature Space=Two-dimensional, Clustering Algorithm=HDBSCAN2026.04 | 0.0501 | 0.4057 | 0.1182 |