Estimating number of clusters on Unstructured Gaussian data D=20
100Success Rate (k=1)Gap (I)
Evaluation results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Gap (I)Reference=BBU2026.03 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| ElbowSig (FDR)Reference=PCA2026.03 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| Gap (I)Reference=PCA2026.03 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| Gap (II)Reference=PCA2026.03 | 100 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| ElbowSig (per-k)Reference=PCA2026.03 | 94 | 0 | 0 | 0 | 2 | 0 | 2 | 0 | 0 | 2 | |
| SigClustReference=Gaussian2026.03 | 92 | — | — | — | — | — | — | — | — | — | |
| ElbowSig (FDR)Reference=BBU2026.03 | 91 | 1 | 0 | 0 | 0 | 1 | 4 | 2 | 0 | 1 | |
| Gap (II)Reference=BBU2026.03 | 90 | 4 | 2 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | |
| ElbowSig (per-k)Reference=BBU2026.03 | 75 | 4 | 3 | 2 | 3 | 2 | 4 | 2 | 2 | 3 |