A survey on unsupervised outlier detection in high‐dimensional numerical data

DOI10.1002/sam.11161OpenAlexW2015887370WikidataQ55894584 ScholiaQ55894584MaRDI QIDQ4969851

Erich Schubert, Arthur Zimek, Hans-Peter Kriegel

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.11161

zbMATH Keywords

curse of dimensionalityanomalies in high-dimensional dataapproximate outlier detectioncorrelation outlier detectionoutlier detection in high-dimensional datasubspace outlier detection

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

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Uses Software

• WEKA
• SOREX
• LOF
• ELKI
• Orca
• SLOM

Cites Work

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