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Comparable Study of Statistical Tests for Virtual Concept Drift Detection

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Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 226))

Abstract

In this paper we examine the possibilities of using popular univariate statistical tests for discovering virtual concept drift in the stream of multidimensional data. Three popular methods are evaluated with different generalization approaches both on simulated and real data and compared by the specificity and sensitivity scores.

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Author information

Authors and Affiliations

  1. Wrocław University of Technology, ul. Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Piotr Sobolewski & Michał Woźniak

Authors
  1. Piotr Sobolewski
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  2. Michał Woźniak
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Corresponding author

Correspondence to Piotr Sobolewski .

Editor information

Editors and Affiliations

  1. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Robert Burduk

  2. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Konrad Jackowski

  3. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Marek Kurzynski

  4. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Michał Wozniak

  5. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St, Wroclaw, 50-370, Poland

    Andrzej Zolnierek

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Sobolewski, P., Woźniak, M. (2013). Comparable Study of Statistical Tests for Virtual Concept Drift Detection. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_32

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  • DOI: https://doi.org/10.1007/978-3-319-00969-8_32

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00968-1

  • Online ISBN: 978-3-319-00969-8

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