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Isolation Forest - nju.edu.cn
Nanjing University, Nanjing 210093, China zhouzh@lamda.nju.edu.cn Abstract Most existing model-based approaches to anomaly de-tection construct a profile of normal instances, then iden-tify instances that do not conform to the normal profile as anomalies. This paper proposes a fundamentally different
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