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Tabular Data Generation On Heloc
Metrics
DT Accuracy
LR Accuracy
Parameters(M)
RF Accuracy
Results
Performance results of various models on this benchmark
| Paper Title | Repository | |||||
|---|---|---|---|---|---|---|
| Distill-GReaT | 81.4 | 70.58 | 82 | 82.14 | Language Models are Realistic Tabular Data Generators | |
| GReaT | 79.1 | 71.9 | 355 | 80.93 | Language Models are Realistic Tabular Data Generators | |
| TVAE | 76.39 | 71.04 | 62 | 77.24 | Modeling Tabular data using Conditional GAN | |
| Binary Diffusion | 70.25 | 71.76 | 2.6 | 70.47 | Tabular Data Generation using Binary Diffusion | |
| CTGAN | 61.34 | 57.72 | 0.277 | 62.35 | Modeling Tabular data using Conditional GAN | |
| CopulaGAN | 42.36 | 42.03 | 0.276 | 42.35 | Modeling Tabular data using Conditional GAN |
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