Clustering on Benchmark dataset repository Third-party labels only v1.1.0
16Cases with AR < 0.8ITM
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| ITM2026.04 | 16 | 7 | 77 | 73 | |
| Single Linkage2026.04 | 16 | 8 | 44 | 48 | |
| Complete Linkage2026.04 | 15 | 6 | 78 | 63 | |
| Adaptive Density Peaks2026.04 | 13 | 8 | 76 | 70 | |
| Ward Linkage2026.04 | 13 | 6 | 72 | 68 | |
| K-means2026.04 | 12 | 9 | 82 | 71 | |
| Birch2026.04 | 11 | 8 | 83 | 70 | |
| Average Linkage2026.04 | 11 | 8 | 91 | 68 | |
| Gaussian Mixture2026.04 | 9 | 10 | 94 | 75 | |
| Spectral2026.04 | 8 | 13 | 96 | 83 | |
| GenieG (Genie parameter)=0.3, M (smoothing parameter)=32026.04 | 7 | 12 | 95 | 86 | |
| GenieG (Genie parameter)=0.3, M (smoothing parameter)=12026.04 | 7 | 12 | 94 | 85 | |
| Lumbermarkf (min_cluster_factor)=0.25, M (smoothing parameter)=12026.04 | 6 | 12 | 94 | 89 | |
| Lumbermarkf (min_cluster_factor)=0.25, M (smoothing parameter)=52026.04 | 4 | 15 | 98 | 91 |