Image Clustering On Fashion Mnist
Metriken
Accuracy
NMI
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Accuracy | NMI |
|---|---|---|
| deep-density-based-image-clustering | 0.619 | 0.682 |
| deep-transformation-invariant-clustering | 0.612 | 0.637 |
| improving-k-means-clustering-performance-with | 0.555 | 0.574 |
| interpretable-visualizations-with | 0.635 | 0.71 |
| scattering-transform-based-image-clustering | 0.628 | 0.644 |
| contrastive-hierarchical-clustering | 0.65 | - |
| selective-pseudo-label-clustering | 0.679 | 0.735 |
| n2dnot-too-deep-clustering-via-clustering-the | 0.672 | 0.684 |
| deep-density-based-image-clustering | 0.609 | 0.661 |
| graph-degree-linkage-agglomerative-clustering | 0.627 | 0.66 |
| deep-clustering-with-a-dynamic-autoencoder | 0.591 | 0.642 |
| deep-clustering-via-probabilistic-ratio-cut | 0.791 | 0.758 |
| the-vampprior-mixture-model | 0.716 | 0.710 |