Anomaly Detection on ADGym Average performance across 14 domains
75.9AUCPRGround Truth (Best Design)
Evaluation Results
| Method | Links | |
|---|---|---|
| Ground Truth (Best Design)Number of labeled anomalies=202023.09 | 75.9 | |
| Ground Truth (Best Design)Number of labeled anomalies=102023.09 | 73.7 | |
| Ground Truth (Best Design)Number of labeled anomalies=52023.09 | 70.6 | |
| ADGym (ML-ensemble)Number of labeled anomalies=20, ML Algorithm=CatBoost2023.09 | 66.9 | |
| ADGym (ML-ensemble)Number of labeled anomalies=20, ML Algorithm=XGBoost2023.09 | 66.2 | |
| ADGym (ML-single)Number of labeled anomalies=20, ML Algorithm=CatBoost2023.09 | 65.7 | |
| ADGym (ML-single)Number of labeled anomalies=20, ML Algorithm=XGBoost2023.09 | 64.2 | |
| ADGym (DL-ensemble)Number of labeled anomalies=20, Meta-feature extraction=2-stage2023.09 | 63.9 | |
| ADGym (DL-ensemble)Number of labeled anomalies=20, Meta-feature extraction=end2end2023.09 | 62.3 | |
| ADGym (DL-single)Number of labeled anomalies=20, Meta-feature extraction=2-stage2023.09 | 62.2 | |
| ADGym (ML-ensemble)Number of labeled anomalies=10, ML Algorithm=XGBoost2023.09 | 61.7 | |
| ADGym (DL-single)Number of labeled anomalies=20, Meta-feature extraction=end2end2023.09 | 61.6 | |
| ADGym (ML-ensemble)Number of labeled anomalies=10, ML Algorithm=CatBoost2023.09 | 61.4 | |
| ADGym (ML-single)Number of labeled anomalies=10, ML Algorithm=CatBoost2023.09 | 60.3 | |
| ADGym (DL-ensemble)Number of labeled anomalies=10, Meta-feature extraction=2-stage2023.09 | 60 | |
| ADGym (ML-single)Number of labeled anomalies=10, ML Algorithm=XGBoost2023.09 | 60 | |
| ADGym (DL-ensemble)Number of labeled anomalies=10, Meta-feature extraction=end2end2023.09 | 59.7 | |
| ADGym (DL-single)Number of labeled anomalies=10, Meta-feature extraction=end2end2023.09 | 59.2 | |
| ADGym (DL-single)Number of labeled anomalies=10, Meta-feature extraction=2-stage2023.09 | 58.9 | |
| ADGym (ML-ensemble)Number of labeled anomalies=5, ML Algorithm=XGBoost2023.09 | 55.3 | |
| Supervised SelectionNumber of labeled anomalies=202023.09 | 55 | |
| ADGym (ML-ensemble)Number of labeled anomalies=5, ML Algorithm=CatBoost2023.09 | 54.7 | |
| ADGym (ML-single)Number of labeled anomalies=5, ML Algorithm=CatBoost2023.09 | 53.9 | |
| ADGym (DL-ensemble)Number of labeled anomalies=5, Meta-feature extraction=2-stage2023.09 | 53.8 | |
| ADGym (DL-ensemble)Number of labeled anomalies=5, Meta-feature extraction=end2end2023.09 | 53.4 | |
| ADGym (DL-single)Number of labeled anomalies=5, Meta-feature extraction=end2end2023.09 | 53.3 | |
| ADGym (ML-single)Number of labeled anomalies=5, ML Algorithm=XGBoost2023.09 | 53.2 | |
| ADGym (DL-single)Number of labeled anomalies=5, Meta-feature extraction=2-stage2023.09 | 53.1 | |
| Random SelectionNumber of labeled anomalies=202023.09 | 50.9 | |
| Random SelectionNumber of labeled anomalies=102023.09 | 47.8 | |
| Supervised SelectionNumber of labeled anomalies=102023.09 | 45.9 | |
| Random SelectionNumber of labeled anomalies=52023.09 | 44.7 | |
| Supervised SelectionNumber of labeled anomalies=52023.09 | 36.5 |