MINIBOONE
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | MiniBooNE 30K subsamples | Accuracy94.21 | 44 | |
| Unconditional density estimation | MINIBOONE (test) | NLL (nats)8.86 | 22 | |
| Density Estimation | MINIBOONE | NLL9.97 | 16 | |
| Dynamic Feature Selection | Miniboone 5-fold CV | AUAC-F186.25 | 13 | |
| Classification | Miniboone | Error Rate4.84 | 11 | |
| Density Estimation | MINIBOONE d=43; N=36,488 (test) | Avg Test Log-Likelihood10.55 | 11 | |
| Classification | MiniBooNE (test) | Mean Test Accuracy75.4 | 10 | |
| Evasion attack verification | miniboone 10,000 examples (test) | Speedup19.2 | 8 | |
| Point-level mislabeled data detection | MiniBooNE | AUCPR0.78 | 7 | |
| Classification | miniboone | Balanced Accuracy94.978 | 7 | |
| Density Estimation | Miniboone d=50 (test) | NLL-0.053 | 5 | |
| Tabular Classification | MiniBooNE | Accuracy (Mean)94.2 | 5 | |
| Unconditional Density Estimation | MINIBOONE UCI (test) | Average CD24.5 | 5 | |
| Generative Modeling | MINIBOONE | FID Score0.878 | 4 | |
| Classification | UCI Miniboo | Training Time (s)77.6 | 3 | |
| Data Selection | MiniBooNE | Accuracy80.4 | 2 | |
| Cell-level outlier detection | MiniBooNE | AUC77 | 2 | |
| Data Selection | MiniBooNE (test) | Accuracy75.3 | 1 | |
| Model Allocation | MiniBooNE | AUC94 | 1 | |
| Wasserstein distance error bound estimation | MiniBooNE | Fournier Distance Estimate (N)11.77 | 1 |
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