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Active Learning Classifier for Streaming Data

  • Michał WoźniakEmail author
  • Bogusław Cyganek
  • Andrzej Kasprzak
  • Paweł Ksieniewicz
  • Krzysztof Walkowiak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9648)

Abstract

This work reports the research on active learning approach applied to the data stream classification. The chosen characteristics of the proposed frameworks were evaluated on the basis of the wide range of computer experiments carried out on the three benchmark data streams. Obtained results confirmed the usability of proposed method to the data stream classification with the presence of incremental concept drift.

Keywords

Pattern classification Data stream classification Active learning 

Notes

Acknowledgement

This work was supported by the Polish National Science Centre under the grant no. DEC-2013/09/B/ST6/02264. This work was supported by EC under FP7, Coordination and Support Action, Grant Agreement Number 316097, ENGINE European Research Centre of Network Intelligence for Innovation Enhancement (http://engine.pwr.wroc.pl/). All computer experiments were carried out using computer equipment sponsored by ENGINE project.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Michał Woźniak
    • 1
    Email author
  • Bogusław Cyganek
    • 2
    • 3
  • Andrzej Kasprzak
    • 1
  • Paweł Ksieniewicz
    • 1
  • Krzysztof Walkowiak
    • 1
  1. 1.Department of Systems and Computer Networks, Faculty of ElectronicsWrocław University of TechnologyWroclawPoland
  2. 2.ENGINE Center, Wrocław University of TechnologyWroclawPoland
  3. 3.AGH University of Science and TechnologyKrakowPoland

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