Clustering on L^2
45.8ARIK-Medoids
Evaluation Results
| Method | Links | |
|---|---|---|
| K-MedoidsSpace=Metric, Train=O(n^2 K), Infer=O(nK), Memory=O(n^2)2026.05 | 45.8 | |
| FDA K-MeansSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 45.1 | |
| FunclustSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 45.1 | |
| Kernel k-GroupsSpace=Metric, Train=O(Kn^2), Memory=O(n^2)2026.05 | 43.8 | |
| fclustSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 43 | |
| FunHDDCSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 41.9 | |
| MMD GMM (Gaussian)Space=Hilbert, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 41.2 | |
| FDA Fuzzy C-MeansSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 39.6 | |
| Projected GMM (Appendix D)Space=Hilbert, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 38.6 | |
| CurvclustSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 38.3 | |
| MMD GMM (Polynomial)Space=Hilbert, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 37.6 | |
| K-CentresSpace=L^2, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 36.1 | |
| Hierarchical (Avg)Space=Metric, Train=O(n^2 log n), Memory=O(n^2)2026.05 | 23.4 | |
| HDBSCANSpace=Metric, Train=O(n), Memory=O(n)2026.05 | 17.1 | |
| K-CenterSpace=Metric, Train=O(nK), Infer=O(nK), Memory=O(n)2026.05 | 15 | |
| DBSCANSpace=Metric, Train=O(n), Memory=O(n)2026.05 | 0 |