Image Clustering On Mnist Full
Metrics
Accuracy
NMI
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy | NMI |
|---|---|---|
| the-vampprior-mixture-model | 0.967 | 0.920 |
| tree-sne-hierarchical-clustering-and | - | 0.864 |
| interpretable-visualizations-with | 0.984 | 0.956 |
| deep-clustering-on-the-link-between | - | 0.913 |
| discriminatively-boosted-image-clustering | 0.976 | 0.937 |
| deep-density-based-image-clustering | 0.986 | 0.961 |
| scattering-transform-based-image-clustering | 0.964 | 0.921 |
| selective-pseudo-label-clustering | 0.992 | 0.975 |
| n2dnot-too-deep-clustering-via-clustering-the | 0.987 | 0.964 |
| joint-unsupervised-learning-of-deep | 0.964 | 0.917 |
| deep-transformation-invariant-clustering | 0.979 | 0.942 |
| deep-clustering-with-a-dynamic-autoencoder | 0.987 | 0.964 |
| balanced-self-paced-learning-for-generative | 0.973 | 0.940 |
| adversarial-deep-embedded-clustering-on-a | 0.990 | 0.971 |
| graph-degree-linkage-agglomerative-clustering | 0.965 | 0.913 |
| oracle-based-active-set-algorithm-for | 0.969 | 0.941 |