Ensembles for unsupervised outlier detection: challenges and research questions

Zimek, Arthur, Campello, Ricardo J.G.B., and Sander, Jörg (2013) Ensembles for unsupervised outlier detection: challenges and research questions. SIGKDD Explorations Newsletter, 15 (1). pp. 11-22.

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Ensembles for unsupervised outlier detection is an emerging topic that has been neglected for a surprisingly long time (although there are reasons why this is more difficult than supervised ensembles or even clustering ensembles). Aggarwal recently discussed algorithmic patterns of outlier detection ensembles, identified traces of the idea in the literature, and remarked on potential as well as unlikely avenues for future transfer of concepts from supervised ensembles. Complementary to his points, here we focus on the core ingredients for building an outlier ensemble, discuss the first steps taken in the literature, and identify challenges for future research.

Item ID: 46774
Item Type: Article (Research - C1)
ISSN: 1931-0153
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SIGKDD: Special Interest Group on Knowledge Discovery in Data

Date Deposited: 10 Mar 2017 01:31
FoR Codes: 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010499 Statistics not elsewhere classified @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 100%
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