Clustering on Molecular
0.151ARIMMD GMM (Polynomial)
Evaluation results
| Method | Links | |
|---|---|---|
| MMD GMM (Polynomial)Space=Hilbert, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 0.151 | |
| Kernel k-GroupsSpace=Metric, Train=O(Kn^2), Memory=O(n^2)2026.05 | 0.125 | |
| HDBSCANSpace=Metric, Train=O(n), Memory=O(n)2026.05 | 0.117 | |
| MMD GMM (Gaussian)Space=Hilbert, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 0.104 | |
| Projected GMM (Appendix D)Space=Hilbert, Train=O(nK), Infer=O(nK), Memory=O(nK)2026.05 | 0.104 | |
| Hierarchical (Avg)Space=Metric, Train=O(n^2 log n), Memory=O(n^2)2026.05 | 0.081 | |
| DBSCANSpace=Metric, Train=O(n), Memory=O(n)2026.05 | 0.074 | |
| K-CenterSpace=Metric, Train=O(nK), Infer=O(nK), Memory=O(n)2026.05 | 0.074 | |
| K-MedoidsSpace=Metric, Train=O(n^2 K), Infer=O(nK), Memory=O(n^2)2026.05 | -0.005 |