Classification on Diabetes (test)
92.5AccuracyAPC-GNN++
Evaluation results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| APC-GNN++2025.12 | 92.5 | — | — | — | — | 91.8 | — | |
| Vanilla GCN2025.12 | 89.3 | — | — | — | — | 88.6 | — | |
| XGBoost2025.12 | 88.1 | — | — | — | — | 87.5 | — | |
| Random Forest2025.12 | 87.6 | — | — | — | — | 86.9 | — | |
| MLP2025.12 | 85.2 | — | — | — | — | 84.7 | — | |
| SLIPBase# Parameters=120M, # Time Points=1.7B, Evaluation Protocol=linear-probing2026.03 | 84.44 | — | — | — | — | — | — | |
| TF-C# Parameters=12M, # Time Points=1.72M, Evaluation Protocol=linear-probing2026.03 | 82.96 | — | — | — | — | — | — | |
| PatchTST (Supervised Learning)# Parameters=0.9M, Evaluation Protocol=Supervised Learning2026.03 | 82.96 | — | — | — | — | — | — | |
| Statistical MLEvaluation Protocol=linear-probing2026.03 | 82.22 | — | — | — | — | — | — | |
| SimMTM# Parameters=0.5M, # Time Points=1.72M, Evaluation Protocol=linear-probing2026.03 | 82.22 | — | — | — | — | — | — | |
| SundialBase# Parameters=128M, # Time Points=1032B, Evaluation Protocol=linear-probing2026.03 | 82.22 | — | — | — | — | — | — | |
| Normwear# Parameters=136M, # Time Points=0.31B, Evaluation Protocol=linear-probing2026.03 | 82.22 | — | — | — | — | — | — | |
| ChatTS# Parameters=8B, # Time Points=0.23B, Evaluation Protocol=linear-probing2026.03 | 82.22 | — | — | — | — | — | — | |
| XBNet2021.06 | 78.78 | — | — | — | — | — | — | |
| OEHGK (inner iterations)=12026.02 | 78.21 | — | — | — | — | — | 0.5404 | |
| ChronosBase# Parameters=200M, # Time Points=12.8B, Evaluation Protocol=linear-probing2026.03 | 77.78 | — | — | — | — | — | — | |
| XGBoost2021.06 | 77.48 | — | — | — | — | — | — | |
| Chronos2# Parameters=120M, # Time Points=242.8B, Evaluation Protocol=linear-probing2026.03 | 77.04 | — | — | — | — | — | — | |
| RHGK (inner iterations)=1282026.02 | 72.82 | — | — | — | — | — | 0.6159 | |
| RHGK (inner iterations)=2562026.02 | 70.51 | — | — | — | — | — | 0.6831 | |
| RHGK (inner iterations)=642026.02 | 68.55 | — | — | — | — | — | 0.622 | |
| BAEN-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 68.4 | — | — | — | — | — | — | |
| BQ-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 67.4 | — | — | — | — | — | — | |
| BALS-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 67 | — | — | — | — | — | — | |
| EN-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 66.5 | — | — | — | — | — | — | |
| ε-BAEN-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 66.3 | — | — | — | — | — | — | |
| ALS-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 66.1 | — | — | — | — | — | — | |
| Pin-SVMKernel=linear, Noise Type=label noise, Noise Level=25%2026.04 | 64.4 | — | — | — | — | — | — | |
| OriginalDownstream model=RF2024.09 | 59 | — | — | — | — | — | — | |
| OriginalDownstream model=LR2024.09 | 58.76 | — | — | — | — | — | — | |
| GReaTDownstream model=RF, Number of parameters=355M2024.09 | 58.34 | — | — | — | — | — | — | |
| Distill-GReaTDownstream model=RF, Number of parameters=82M2024.09 | 58.03 | — | — | — | — | — | — | |
| Binary DiffusionDownstream model=LR, Number of parameters=1.8M2024.09 | 57.75 | — | — | — | — | — | — | |
| Binary DiffusionDownstream model=RF, Number of parameters=1.8M2024.09 | 57.52 | — | — | — | — | — | — | |
| GReaTDownstream model=LR, Number of parameters=355M2024.09 | 57.34 | — | — | — | — | — | — | |
| Distill-GReaTDownstream model=LR, Number of parameters=82M2024.09 | 57.33 | — | — | — | — | — | — | |
| OriginalDownstream model=DT2024.09 | 57.29 | — | — | — | — | — | — | |
| Binary DiffusionDownstream model=DT, Number of parameters=1.8M2024.09 | 57.13 | — | — | — | — | — | — | |
| TVAEDownstream model=LR, Number of parameters=369K2024.09 | 56.34 | — | — | — | — | — | — | |
| GReaTDownstream model=DT, Number of parameters=355M2024.09 | 55.23 | — | — | — | — | — | — | |
| TVAEDownstream model=RF, Number of parameters=369K2024.09 | 55.17 | — | — | — | — | — | — | |
| Distill-GReaTDownstream model=DT, Number of parameters=82M2024.09 | 54.1 | — | — | — | — | — | — | |
| TVAEDownstream model=DT, Number of parameters=369K2024.09 | 53.3 | — | — | — | — | — | — | |
| CTGANDownstream model=RF, Number of parameters=9.6M2024.09 | 52.23 | — | — | — | — | — | — | |
| CTGANDownstream model=LR, Number of parameters=9.6M2024.09 | 50.93 | — | — | — | — | — | — | |
| CTGANDownstream model=DT, Number of parameters=9.6M2024.09 | 49.73 | — | — | — | — | — | — | |
| CopulaGANDownstream model=LR, Number of parameters=9.4M2024.09 | 40.27 | — | — | — | — | — | — | |
| CopulaGANDownstream model=DT, Number of parameters=9.4M2024.09 | 38.5 | — | — | — | — | — | — | |
| CopulaGANDownstream model=RF, Number of parameters=9.4M2024.09 | 37.59 | — | — | — | — | — | — | |
| +CopulaGAN#syn=+10K2024.04 | — | 54.27 | 41.59 | 59.73 | 59.97 | — | — | |
| +CTAB-GAN#syn=+10K2024.04 | — | 54.22 | 41.53 | 59.73 | 59.91 | — | — | |
| +CTAB-GAN+#syn=+10K2024.04 | — | 54.24 | 41.52 | 59.63 | 60.01 | — | — | |
| +CTGAN#syn=+10K2024.04 | — | 54.72 | 41.92 | 59.86 | 60.63 | — | — | |
| +GReaT#syn=+10K2024.04 | — | 54.78 | 41.98 | 59.98 | 60.61 | — | — | |
| +Ours#syn=+10K2024.04 | — | 54.94 | 42.14 | 60.04 | 60.82 | — | — | |
| +TabDDPM#syn=+10K2024.04 | — | 54.64 | 41.83 | 59.91 | 60.55 | — | — | |
| +TVAE#syn=+10K2024.04 | — | 54.79 | 41.96 | 59.96 | 60.71 | — | — | |
| all-featCategory=Non-causal, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 79.06 | — | — | — | — | — | |
| borutaCategory=Non-causal, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 77.79 | — | — | — | — | — | |
| causal-obsCategory=Causal-observation, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 79.06 | — | — | — | — | — | |
| causal-skCategory=Causal-interventional, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 81 | — | — | — | — | — | |
| chi-sqCategory=Non-causal, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 79.06 | — | — | — | — | — | |
| miCategory=Non-causal, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 80.26 | — | — | — | — | — | |
| MMMBCategory=Causal-observation, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 79.06 | — | — | — | — | — | |
| Original#syn=02024.04 | — | 54.87 | 42.07 | 60 | 60.73 | — | — | |
| spearmanCategory=Non-causal, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 76.18 | — | — | — | — | — | |
| STMBCategory=Causal-observation, Evaluation=4-fold cross-validation, Selection=Best-sparse feature set2026.06 | — | 79.06 | — | — | — | — | — |