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Models/IsoForest

IsoForest

Reported on 8 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

Anomaly DetectiononAnoShift
ROC-AUC FAR· 2022-06-30
27.16
best: 62.5 (ACR-NTL (zero-shot, test anomaly ratio=1%))
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476
Anomaly DetectiononAnoShift
ROC-AUC IID· 2022-06-30
86.09
best: 92.67 (deepSVDD)
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476
Anomaly DetectiononAnoShift
ROC-AUC NEAR· 2022-06-30
75.26
best: 87 (deepSVDD)
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476
Anomaly DetectiononAnoShift
ROC-AUC-ID (In-Distribution setup)· 2022-06-30
81.27
best: 88.24 (deepSVDD)
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476

Graphs4 results

Unsupervised Anomaly DetectiononAnoShift
ROC-AUC FAR· 2022-06-30
27.16
best: 62.5 (ACR-NTL (zero-shot, test anomaly ratio=1%))
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476
Unsupervised Anomaly DetectiononAnoShift
ROC-AUC IID· 2022-06-30
86.09
best: 92.67 (deepSVDD)
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476
Unsupervised Anomaly DetectiononAnoShift
ROC-AUC NEAR· 2022-06-30
75.26
best: 87 (deepSVDD)
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476
Unsupervised Anomaly DetectiononAnoShift
ROC-AUC-ID (In-Distribution setup)· 2022-06-30
81.27
best: 88.24 (deepSVDD)
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection arXiv:2206.15476