A survey of outlier detection methodologies

Hodge, V.J. orcid.org/0000-0002-2469-0224 and Austin, J. orcid.org/0000-0001-5762-8614 (2004) A survey of outlier detection methodologies. Artificial Intelligence Review. pp. 85-126. ISSN 1573-7462



Copyright, Publisher and Additional Information: Copyright © 2004 Kluwer Academic Publishers. This is an author produced version of a paper published in Artificial Intelligence Review. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination.The original publication is available at www.springerlink.com.
Keywords: anomaly,detection,deviation,noise,novelty,outlier,recognition,NOVELTY DETECTION
  • Published: October 2004
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Sherpa Assistant
Date Deposited: 08 Nov 2005
Last Modified: 07 Sep 2022 09:08
Published Version: https://doi.org/10.1023/B:AIRE.0000045502.10941.a9
Status: Published
Refereed: Yes
Identification Number: https://doi.org/10.1023/B:AIRE.0000045502.10941.a9
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