Principal Component Analysis on Synthetic Gaussian data d=900, n=1000 (test)
14.2Runtime (ms)MS-PCA
Evaluation Results
| Method | Links | |
|---|---|---|
| MS-PCANumber of Leading Principal Components=1 PC2026.05 | 14.2 | |
| MS-PCANumber of Leading Principal Components=9 PCs2026.05 | 19.2 | |
| RPCA-AAPNumber of Leading Principal Components=1 PC2026.05 | 79 | |
| RPCA-AAPNumber of Leading Principal Components=9 PCs2026.05 | 99.6 | |
| TylerNumber of Leading Principal Components=1 PC2026.05 | 172 | |
| TylerNumber of Leading Principal Components=9 PCs2026.05 | 174 | |
| HuberNumber of Leading Principal Components=1 PC2026.05 | 3,860 | |
| HuberNumber of Leading Principal Components=9 PCs2026.05 | 3,860 | |
| ℓ1-PCANumber of Leading Principal Components=1 PC2026.05 | 8,230 |