Tabular Data Generation On Diabetes
Métriques
DT Accuracy
LR Accuracy
Parameters(M)
RF Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | DT Accuracy | LR Accuracy | Parameters(M) | RF Accuracy | Paper Title | Repository |
|---|---|---|---|---|---|---|
| Distill-GReaT | 0.541 | 0.5733 | 82 | 0.5803 | Language Models are Realistic Tabular Data Generators | |
| CTGAN | 0.4973 | 0.5093 | 9.6 | 0.5223 | Modeling Tabular data using Conditional GAN | |
| Binary Diffusion | 0.5713 | 0.5775 | 1.8 | 0.5752 | Tabular Data Generation using Binary Diffusion | |
| GReaT | 0.5523 | 0.5734 | 355 | 0.5834 | Language Models are Realistic Tabular Data Generators | |
| TVAE | 0.5330 | 0.5634 | 0.359 | 0.5517 | Modeling Tabular data using Conditional GAN | |
| CopulaGAN | 0.385 | 0.4027 | 9.4 | 0.3759 | Modeling Tabular data using Conditional GAN |
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