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This document presents a novel anomaly detection method called isolation using Nearest Neighbor Ensemble (iNNE) that addresses the limitations of the existing isolation-based detector, iForest. iNNE improves detection of local anomalies and performs efficiently with linear time complexity, making it suitable for large and high-dimensional datasets. The proposed method utilizes hyperspheres for isolation, adapting to local data distributions, which enhances its effectiveness compared to traditional axis-para

Author
alihassan
Language
EN