Classification on Credit
98.6ROCAUCNODE-GA2M
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| NODE-GA2MInterpretability=Yes, Complex.=O(n^2)2026.02 | 98.6 | — | — | — | — | — | |
| NeuralSPAMOrder=22022.05 | 98.5 | — | — | — | — | — | |
| NA2MInterpretability=Yes, Complex.=O(n^2)2026.02 | 98.5 | — | — | — | — | — | |
| LinearSPAMOrder=22022.05 | 98.36 | — | — | — | — | — | |
| EB2MInterpretability=Yes, Complex.=O(n^2)2026.02 | 98.2 | — | — | — | — | — | |
| SplineInterpretability=Yes, Complex.=O(n)2026.02 | 98.2 | — | — | — | — | — | |
| NAEInterpretability=Yes, Complex.=O(n)2026.02 | 98.2 | — | — | — | — | — | |
| NODE-GAM2022.05 | 98.1 | — | — | — | — | — | |
| MLPInterpretability=No, Complex.=N/A2026.02 | 98.1 | — | — | — | — | — | |
| NODEInterpretability=No, Complex.=N/A2026.02 | 98.1 | — | — | — | — | — | |
| NBMInterpretability=Yes, Complex.=O(n)2026.02 | 98.1 | — | — | — | — | — | |
| NODE-GAMInterpretability=Yes, Complex.=O(n)2026.02 | 98.1 | — | — | — | — | — | |
| XGBoost2022.05 | 97.8 | — | — | — | — | — | |
| XGBoostInterpretability=No, Complex.=N/A2026.02 | 97.8 | — | — | — | — | — | |
| NB2MInterpretability=Yes, Complex.=O(n^2)2026.02 | 97.8 | — | — | — | — | — | |
| NAMInterpretability=Yes, Complex.=O(n)2026.02 | 97.7 | — | — | — | — | — | |
| NAM2022.05 | 97.66 | — | — | — | — | — | |
| LinearInterpretability=Yes, Complex.=O(n)2026.02 | 97.6 | — | — | — | — | — | |
| EBMInterpretability=Yes, Complex.=O(n)2026.02 | 97.4 | — | — | — | — | — | |
| EurekaLLM Backbone=gpt4o2026.05 | 83.8 | — | — | — | — | — | |
| EurekaLLM Backbone=32B2026.05 | 82.4 | — | — | — | — | — | |
| EurekaLLM Backbone=grok22026.05 | 81.5 | — | — | — | — | — | |
| CAAFE2026.05 | 79.7 | — | — | — | — | — | |
| EurekaLLM Backbone=Qwen2026.05 | 79.4 | — | — | — | — | — | |
| TabPFN2026.05 | 78.7 | — | — | — | — | — | |
| DirectAugClassifier Architecture=MLP22025.05 | 75.4 | 73.2 | — | — | — | 54.1 | |
| REFINEClassifier Architecture=MLP12025.05 | 74.5 | 74 | — | — | — | 52 | |
| FeatLLM2026.05 | 74.3 | — | — | — | — | — | |
| DirectAugClassifier Architecture=MLP12025.05 | 73.8 | 73.5 | — | — | — | 52.4 | |
| REFINEClassifier Architecture=MLP22025.05 | 73.6 | 72.6 | — | — | — | 53.5 | |
| RawClassifier Architecture=MLP12025.05 | 73 | 72.3 | — | — | — | 49 | |
| RawClassifier Architecture=MLP22025.05 | 72.5 | 71.7 | — | — | — | 51.5 | |
| DFS2026.05 | 70.7 | — | — | — | — | — | |
| OpenFe2026.05 | 70.1 | — | — | — | — | — | |
| DP-FinDiffε-DP=102025.11 | 69.7 | — | — | — | — | — | |
| AutoFe2026.05 | 67.6 | — | — | — | — | — | |
| DP-FinDiffε-DP=12025.11 | 67.4 | — | — | — | — | — | |
| Real2022.02 | 67 | 61 | 48 | 61 | 0 | — | |
| augmented no-clipping DP-GDModel=Model 2, Privacy budget=ε = 1, δ = 10−5, Number of runs=1002026.05 | 65.01 | 78.28 | — | — | — | — | |
| standard DP-GDModel=Model 1, Privacy budget=ε = 1, δ = 10−5, Number of runs=1002026.05 | 64.11 | 77.95 | — | — | — | — | |
| DP-TVAEε-DP=102025.11 | 63.7 | — | — | — | — | — | |
| DP model using output perturbationModel=Model 3, Privacy budget=ε = 1, δ = 10−5, Number of runs=1002026.05 | 60.12 | 76.57 | — | — | — | — | |
| PrivBN2022.02 | 60 | 51 | 32 | 51 | 393,000 | — | |
| IT-GAN(Q)variant=Quantized2022.02 | 60 | 54 | 41 | 54 | 362,000 | — | |
| IT-GAN(L)variant=Linear2022.02 | 60 | 55 | 40 | 55 | 529,000 | — | |
| TGAN2022.02 | 59 | 55 | 40 | 55 | 236,000 | — | |
| IT-GANvariant=Standard2022.02 | 59 | 54 | 40 | 54 | 238,000 | — | |
| DP-FinDiffε-DP=0.22025.11 | 58.3 | — | — | — | — | — | |
| TVAE2022.02 | 58 | 57 | 39 | 57 | 465,000 | — | |
| CLBN2022.02 | 56 | 48 | 34 | 48 | 1,850,000 | — | |
| MedGAN2022.02 | 56 | 51 | 37 | 51 | 19,500,000 | — | |
| DP-TabDDPMε-DP=102025.11 | 55.9 | — | — | — | — | — | |
| TableGAN2022.02 | 54 | 47 | 35 | 47 | 208,000 | — | |
| VeeGAN2022.02 | 54 | 48 | 36 | 48 | 1,850,000 | — | |
| DP-TabDDPMε-DP=12025.11 | 52.4 | — | — | — | — | — | |
| Ind2022.02 | 51 | 44 | 27 | 44 | 11,300 | — | |
| Uniform2022.02 | 50 | 34 | 24 | 34 | 18,900,000 | — | |
| DP-TVAEε-DP=0.22025.11 | 49.5 | — | — | — | — | — | |
| DP-CTGANε-DP=0.22025.11 | 49.5 | — | — | — | — | — | |
| DP-TabDDPMε-DP=0.22025.11 | 48.9 | — | — | — | — | — | |
| DP-CTGANε-DP=102025.11 | 48.7 | — | — | — | — | — | |
| DP-CTGANε-DP=12025.11 | 48.6 | — | — | — | — | — | |
| DP-TVAEε-DP=12025.11 | 47.7 | — | — | — | — | — | |
| CatBoostScenario=Non-strategic2026.05 | — | 78.97 | — | — | — | — | |
| CatBoostScenario=Strategic2026.05 | — | 74.65 | — | — | — | — | |
| Chunked TabPFNScenario=Non-strategic2026.05 | — | 80.9 | — | — | — | — | |
| Chunked TabPFNScenario=Strategic2026.05 | — | 74.9 | — | — | — | — | |
| Drift-Resilient TabPFNScenario=Non-strategic2026.05 | — | 79.8 | — | — | — | — | |
| Drift-Resilient TabPFNScenario=Strategic2026.05 | — | 75.4 | — | — | — | — | |
| KANFLOPs=3474, Param=8642025.06 | — | 74.31 | — | — | — | — | |
| LightGBMScenario=Non-strategic2026.05 | — | 78.28 | — | — | — | — | |
| LightGBMScenario=Strategic2026.05 | — | 74.96 | — | — | — | — | |
| Linear modelsScenario=Non-strategic2026.05 | — | 75.83 | — | — | — | — | |
| Linear modelsScenario=Strategic2026.05 | — | 71.26 | — | — | — | — | |
| MLPFLOPs=608, Param=3302025.06 | — | 73.41 | — | — | — | — | |
| MLPScenario=Non-strategic2026.05 | — | 76.83 | — | — | — | — | |
| MLPScenario=Strategic2026.05 | — | 73.06 | — | — | — | — | |
| NS-SRFLOPs=1184, Param=6182025.06 | — | 74.41 | — | — | — | — | |
| NS-TDFLOPs=1760, Param=9062025.06 | — | 74.71 | — | — | — | — | |
| SPNScenario=Non-strategic2026.05 | — | 80.13 | — | — | — | — | |
| SPNScenario=Strategic2026.05 | — | 80.32 | — | — | — | — | |
| SVMScenario=Non-strategic2026.05 | — | 75.31 | — | — | — | — | |
| SVMScenario=Strategic2026.05 | — | 70.94 | — | — | — | — | |
| TabDPTScenario=Non-strategic2026.05 | — | 79.88 | — | — | — | — | |
| TabDPTScenario=Strategic2026.05 | — | 74.11 | — | — | — | — | |
| TabFlexScenario=Non-strategic2026.05 | — | 79.53 | — | — | — | — | |
| TabFlexScenario=Strategic2026.05 | — | 73.61 | — | — | — | — | |
| TabICLScenario=Non-strategic2026.05 | — | 80.12 | — | — | — | — | |
| TabICLScenario=Strategic2026.05 | — | 74.37 | — | — | — | — | |
| TabPFN v2.5Scenario=Non-strategic2026.05 | — | 80.54 | — | — | — | — | |
| TabPFN v2.5Scenario=Strategic2026.05 | — | 74.83 | — | — | — | — | |
| XGBoostScenario=Non-strategic2026.05 | — | 77.41 | — | — | — | — | |
| XGBoostScenario=Strategic2026.05 | — | 75.12 | — | — | — | — |