MI
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Regression | MI | Negative RMSE-0.892 | 29 | |
| Regression | MI 50% corrupted features noise | Negative RMSE-0.892 | 21 | |
| EEG Classification | MI (test) | Accuracy74.71 | 17 | |
| Feature Selection | MI with random extraneous features | Precision0.993 | 17 | |
| Feature Selection | MI with random extraneous features | ROC AUC100 | 17 | |
| Regression | MI 75% corrupted features noise | Negative RMSE-0.895 | 10 | |
| Time Series Classification | MI | Accuracy91.8 | 10 | |
| Tabular Classification | MI (test) | MLE Score93.8 | 5 | |
| Synthetic Tabular Data Generation | MI | DCR0.026 | 2 |
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