Abalone
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Conditional Shapley value estimation | Abalone cont (M=7) | MSE1.135 | 44 | |
| Conditional Shapley value estimation | Abalone M=8 (all) | MSEv1.142 | 39 | |
| Imbalanced Classification | abalone 19 | F1-Score62.7 | 25 | |
| Imbalanced Classification | abalone | F1-Score61.5 | 25 | |
| Binary Classification | Abalone 1% | PR AUC5.6 | 24 | |
| Regression | Abalone | RMSE2.051 | 22 | |
| Downstream performance prediction | Abalone corrupted with Laplace noise | Downstream Performance95.7 | 19 | |
| Regression | Abalone | MSE0.4408 | 18 | |
| Anomaly Detection | Abalone | AUC-ROC81.44 | 16 | |
| Regression | Abalone (test) | L2 Risk5.01 | 14 | |
| Imbalanced Classification | Abalone 1% | PR AUC5.3 | 12 | |
| Regression | Abalone UCI (test) | RMSE1.949 | 12 | |
| Regression | abalone | Mean MSE4.36 | 12 | |
| Anomaly Detection | abalone | AUPRC89.03 | 10 | |
| Anomaly Detection | abalone In-Domain | F1 Score82.29 | 10 | |
| Binary Classification | abalone | Accuracy89.7 | 10 | |
| Regression | Abalone | MAE1.524 | 10 | |
| Membership Inference Attack | Abalone | AUC-ROC62 | 10 | |
| Clustering | abalone | F-measure68.55 | 9 | |
| Downstream Regression | Abalone | ML Efficiency3.313 | 9 | |
| Clustering | Abalone | ARI12.95 | 9 | |
| Clustering | Abalone | SS Score0.406 | 8 | |
| Classification | Abalone19 | F1 Score22 | 8 | |
| Anomaly Detection | Abalone | F1-Score68 | 8 | |
| Synthetic Data Generation | Abalone Age | Average Runtime (seconds)0.0662 | 6 |
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