Clustering on MULTI-FEAT
93AMICluProp
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CluPropkNN type=exact kNN, Clustering algorithm=Leiden, Distance metric=cosine2026.05 | 93 | 93 | |
| DBHDDistance metric=cosine2026.05 | 91 | 91 | |
| MDT-BSC2025.12 | 87.32 | — | |
| MDT-DIRECT2025.12 | 85.37 | — | |
| MDT-CVX-RAND2025.12 | 84.84 | — | |
| ID2025.12 | 83.43 | — | |
| DPADistance metric=cosine2026.05 | 83 | 80 | |
| AD2025.12 | 82.98 | — | |
| MVD2025.12 | 82.51 | — | |
| P-AD2025.12 | 81.88 | — | |
| MDT-RAND2025.12 | 80.28 | — | |
| CR-DIFF2025.12 | 76.93 | — | |
| DPCDistance metric=cosine2026.05 | 76 | 66 | |
| SCDistance metric=cosine2026.05 | 70 | 60 | |
| hDbscanDistance metric=cosine2026.05 | 68 | 5 | |
| SpecAClDistance metric=cosine2026.05 | 65 | 44 | |
| DbscanDistance metric=cosine2026.05 | 33 | 5 | |
| OpticsDistance metric=cosine2026.05 | 31 | 5 |