Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection

Research article (Engineering Applications of Artificial Intelligence, 2023) · cited 16× · AI/ML
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Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection

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Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection. Retrieved May 24, 2026, from https://4ort.xyz/entity/bayesian-active-learning-isolation-forest-b-alif-a-weakly-supervised-strategy-for-anomaly-detection
MLA “Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/bayesian-active-learning-isolation-forest-b-alif-a-weakly-supervised-strategy-for-anomaly-detection.
BibTeX @misc{4ortxyz_bayesian-active-learning-isolation-forest-b-alif-a-weakly-supervised-strategy-for-anomaly-detection_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection}}, year = {2026}, url = {https://4ort.xyz/entity/bayesian-active-learning-isolation-forest-b-alif-a-weakly-supervised-strategy-for-anomaly-detection}, note = {Accessed: 2026-05-24}}
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