kNN Classification on Fashion-MNIST
84.1AccuracyBH-t-SNE
Evaluation results
| Method | Links | |
|---|---|---|
| BH-t-SNEk=5, cross-validation=5-fold2026.05 | 84.1 | |
| openTSNEk=5, cross-validation=5-fold2026.05 | 84 | |
| t-SNEk=1002018.02 | 81.8 | |
| t-SNEk=2002018.02 | 81 | |
| LargeVisk=1002018.02 | 80.8 | |
| LargeVisk=2002018.02 | 80.5 | |
| t-SNEk=4002018.02 | 80.1 | |
| LargeVisk=4002018.02 | 79.6 | |
| UMAPk=1002018.02 | 79 | |
| UMAPk=2002018.02 | 78.5 | |
| t-SNEk=8002018.02 | 78.4 | |
| UMAPk=4002018.02 | 78 | |
| LargeVisk=8002018.02 | 77.1 | |
| UMAPk=8002018.02 | 76.7 | |
| UMAPk=5, cross-validation=5-fold2026.05 | 75.9 | |
| t-SNEk=16002018.02 | 75.4 | |
| UMAPk=16002018.02 | 74.7 | |
| FastUMAPk=5, cross-validation=5-fold2026.05 | 74.7 | |
| LargeVisk=16002018.02 | 74.2 | |
| SUDEk=5, cross-validation=5-fold2026.05 | 74.2 | |
| UMAPk=32002018.02 | 73 | |
| t-SNEk=32002018.02 | 72.7 | |
| LargeVisk=32002018.02 | 72.6 | |
| NeuralLSH2024.11 | 68.2 | |
| E2E2024.11 | 67.2 | |
| KMeans2024.11 | 66.2 | |
| Laplacian Eigenmapsk=1002018.02 | 63.1 | |
| Laplacian Eigenmapsk=2002018.02 | 62.4 | |
| Laplacian Eigenmapsk=4002018.02 | 61.2 | |
| Laplacian Eigenmapsk=8002018.02 | 60 | |
| Laplacian Eigenmapsk=16002018.02 | 58 | |
| PCAk=2002018.02 | 56.5 | |
| PCAk=1002018.02 | 56.4 | |
| PCAk=4002018.02 | 56.4 | |
| PCAk=8002018.02 | 56 | |
| PCAk=16002018.02 | 55 | |
| Laplacian Eigenmapsk=32002018.02 | 54.2 | |
| PCAk=32002018.02 | 53.3 | |
| ITQ2024.11 | 42.7 | |
| LSH2024.11 | 30.2 |