Wisconsin
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Node Classification | Wisconsin | Accuracy96 | 410 | |
| Node classification | Wisconsin (test) | Mean Accuracy94.89 | 198 | |
| Node Classification | Wisconsin (48/32/20) | Mean Accuracy92.54 | 50 | |
| Node Classification | Wisconsin H=0.19 | Accuracy82.15 | 39 | |
| node classification | wisconsin | Micro F112.8 | 32 | |
| Node Classification | Wisconsin (60%/20%/20%) | Test Accuracy97 | 28 | |
| Node Classification | Wisconsin standard (test) | Accuracy87.65 | 23 | |
| Node Classification | Wisconsin (10 splits) | Accuracy89.41 | 22 | |
| Node Classification | Wisconsin (fixed) | Accuracy88.43 | 21 | |
| Node classification | Wisconsin (Wis.) | Accuracy87.6 | 20 | |
| Link Prediction | Wisconsin Attributed | AUC82.5 | 18 | |
| Node clustering | Wisconsin (test) | Conductance0.52 | 15 | |
| Node Classification | Wisconsin original (test) | Accuracy85.01 | 14 | |
| Node Classification | Wisconsin heterophilic (test) | Accuracy82.31 | 12 | |
| Link Prediction | Wisconsin (test) | Accuracy71.77 | 11 | |
| Node Classification | Wisconsin full-supervised | Accuracy81.57 | 11 | |
| Node Classification | Wisconsin Heterophilic (10 train val test splits) | Accuracy87.65 | 8 | |
| Node Classification | Wisconsin | Avg Model Evaluations5 | 7 | |
| Classification | wisconsin | Accuracy97.5 | 7 | |
| Classification | wis (Wisconsin) (test) | Average Test Error Rate2.4 | 7 | |
| Node Classification | Wisconsin perturbed (test) | Accuracy59.25 | 6 | |
| Node Classification | Wisconsin clean (test) | Accuracy60.5 | 6 | |
| Community Detection | Wisconsin | Precision40 | 5 | |
| Counterfactual Explanation Generation | wisconsin | Validity1 | 4 | |
| Outlier Explanation | wisconsin | Avg Run Time (s)0.0026 | 4 |
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