Sea
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Drift Detection | SEA 30 batches | Accuracy84.46 | 21 | |
| Drift Detection | SEA 20 batches | Accuracy84.62 | 21 | |
| Drift Detection | SEA 10 batches | Accuracy83.37 | 21 | |
| Concept Drift Detection | SEA1 abrupt | MTD48 | 13 | |
| Concept Drift Detection | SEA0 abrupt | MTD (Steps/Samples)43 | 13 | |
| Counterfactual Explanations | SEA (final-checkpoint) | Validation Score100 | 12 | |
| Anomaly Detection | Sea Synthetic (full stream) | G-mean0.88 | 11 | |
| Anomaly Detection | Sea Synthetic | Specificity100 | 11 | |
| Anomaly Detection | Sea | Recall99.9 | 11 | |
| Anomaly Detection | Sea | Average PAUC0.941 | 11 | |
| Streaming Class-Incremental Learning | Sea | EN Accuracy99.7 | 10 | |
| Multi-class Classification | Sea Synthetic | Avg G-mean0.956 | 10 | |
| Data Stream Classification | SEA | Accuracy97.42 | 7 | |
| Symbolic Distillation | SEA 50000 | Mean R^20.3985 | 3 |
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