Friedman
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Regression | Friedman 10 | RMSE0.0484 | 36 | |
| Regression | Friedman 5 | RMSE0.0729 | 36 | |
| Model Compression | friedman 1 | Performance97.2 | 13 | |
| Model Compression | friedman 1 | Accuracy / R2 Score97 | 13 | |
| Regression | friedman 1 | R^286 | 12 | |
| RF compression | friedman 1 | Performance86.3 | 12 | |
| Regression | Friedman Correlated (test) | RMSE1.049 | 12 | |
| Regression | Friedman Uncorrelated (test) | RMSE1.106 | 12 | |
| Regression | Friedman 10 | Negative Log Predictive Density2.83 | 12 | |
| Regression | Friedman 5 | Neg Log Pred Density2.96 | 12 | |
| Regression | Friedman Batch 30 | RMSE1.9371 | 9 | |
| Regression | Friedman Batch 20 | RMSE1.8544 | 9 | |
| Regression | Friedman Batch 10 | RMSE1.9068 | 9 | |
| Regression | Friedman | RMSE1.513 | 8 | |
| Regression | Friedman | MAPE8.33 | 8 | |
| Regression | Friedman 500 points (test) | R291 | 6 | |
| Regression | Friedman 500 points (train) | R20.99 | 6 | |
| Contextual Bandit Simulation | Friedman3 | Final Cumulative Regret422.7 | 6 | |
| Contextual Bandit Simulation | Friedman 2 | Final Cumulative Regret134.6 | 6 | |
| Contextual Bandit Simulation | Friedman | Final Cumulative Regret687.8 | 6 | |
| Contextual Bandit Simulation | Friedman Heteroscedastic | Cumulative Regret715.5 | 6 | |
| Contextual Bandit Simulation | Friedman Sparse | Final Cumulative Regret814.2 | 6 | |
| Contextual Bandit Simulation | Friedman Sparse and Disjoint | Final Cumulative Regret660.1 | 6 | |
| Predictive Density Estimation | Friedman 10 Laplace noise 15% Corruptions | Negative Log Predictive Density-1.44 | 6 | |
| Predictive Density Estimation | Friedman 10 Student-t noise 15% Corruptions | Neg Log Pred Density-1.4 | 6 |
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