Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection

Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo

Neural Information Processing Systems 

In this paper we are concerned with investigating theperformance ofNN-based methods foranomaly detection. We firstshowthrough extensivesimulations thatNNmethods compare favorably to some of the other state-of-the-art algorithms for anomaly detection based on a setofbenchmark syntheticdatasets.

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