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Fluctuation-based Outlier Detection
[article]
2022
arXiv
pre-print
Outlier detection is an important topic in machine learning and has been used in a wide range of applications. Outliers are objects that are few in number and deviate from the majority of objects. As a result of these two properties, we show that outliers are susceptible to a mechanism called fluctuation. This article proposes a method called fluctuation-based outlier detection (FBOD) that achieves a low linear time complexity and detects outliers purely based on the concept of fluctuation
arXiv:2204.10007v1
fatcat:gvyqognxqjaq7mucor6fjk4xai