Clustering on Generated Dataset sparse clusters, 10 dimensions each type, 0.15 deviation 1.0 (test)
202.114Calinski Harabasz ScorePretopo-PaCMAP
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Pretopo-PaCMAPreduction_method=PaCMAP2025.11 | 202.114 | 0.191 | 0.19 | 1.848 | |
| Kamila2025.11 | 184.963 | 0.15 | 0.132 | 2.117 | |
| ClustMD2025.11 | 184.929 | 0.15 | 0.132 | 2.109 | |
| K-Prototypes2025.11 | 181.246 | 0.148 | 0.128 | 2.145 | |
| MixtComp2025.11 | 169.897 | 0.142 | 0.144 | 2.204 | |
| Modha-Spangler2025.11 | 169.793 | 0.143 | 0.145 | 2.202 | |
| Pretopo-UMAPreduction_method=UMAP2025.11 | 162.758 | 0.136 | 0.135 | 2.261 | |
| DenseClus2025.11 | 133.9 | 0.144 | 0.142 | 2.987 | |
| PretopoMDreduction_method=MD2025.11 | 17.02 | -0.032 | -0.055 | 2.8 | |
| Phillip & Ottaway2025.11 | 5.673 | 0.1 | 0.157 | 2.558 | |
| Pretopo-FAMDreduction_method=FAMD2025.11 | 1.199 | 0.017 | 0.026 | 2.16 |