fertility
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Binary Classification | fertility | F1-score94.6 | 35 | |
| Classification | fertility | Accuracy89 | 28 | |
| Binary classification | fertility UCI (test) | Accuracy91 | 27 | |
| Binary Classification | fertility | Accuracy91 | 21 | |
| Classification | fertility 25% feature noise | Accuracy90 | 14 | |
| Classification | fertility 25% label noise (test) | Accuracy89 | 14 | |
| Classification | Fertility 80% (train) | VI34.3 | 8 | |
| Classification | Fertility UCI (test 20%) | VI6.6 | 8 | |
| Automated Data Science | fertility BLADE | BLADE Average Score8.8 | 8 | |
| Classification | fertility 0% noise (test) | Accuracy91 | 7 | |
| Classification | fertility 0% noise | F1-score94.1 | 7 | |
| Classification | fertility (test) | Accuracy89 | 7 | |
| Classification | fertility 25% feature noise | F1 Score94.6 | 7 | |
| Classification | fertility 25% label noise | F1 Score94.1 | 7 | |
| Binary Classification | fertility 25% label noise | Mean F1-score94.1 | 7 | |
| Classification | fertility 25% feature noise (test) | F1 Score94.1 | 7 | |
| Binary Classification | fertility 25% feature noise (test) | Accuracy89 | 7 | |
| Binary Classification | fertility 0% noise | Accuracy89 | 7 | |
| Binary Classification | fertility 25% feature noise | F1 Score95.2 | 7 | |
| Regression | Fertility | Mean % Improvement in MSE (vs RF(10))13.08 | 6 | |
| Classification | fertility UCI/KEEL (test) | Accuracy0.8689 | 6 | |
| Classification | fertility 80%-20% (train test) | Accuracy80 | 4 |
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