Explainable Distance-Based Outlier Detection in Data Streams

Explaining outliers is a topic that attracts a lot of interest; however existing proposals focus on the identification of the relevant dimensions. We extend this rationale for unsupervised distance-based outlier detection, and through investigating subspaces, we propose a novel labeling of outliers...

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Hlavní autoři: Theodoros Toliopoulos, Anastasios Gounaris
Médium: Artigo
Jazyk:Inglês
Vydáno: IEEE 2022-01-01
Edice:IEEE Access
Témata:
Data streams
distance-based outlier detection
distributed
explainability
flink
On-line přístup:https://ieeexplore.ieee.org/document/9766336/
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