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A First Attempt on Online Data Stream Classifier Using Context

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Data Mining and Big Data (DMBD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

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Abstract

The big data is characterized by 4Vs (volume, velocity, variety, and variability). In this paper we focus on the velocity, but actually it usually comes together with volume. It means, that the crucial problem of the contemporary data analytics is to answer the question how to discover useful knowledge from fast incoming data. The paper presents an online data stream classification method, which adapts the classification with context to recognize incoming examples and additionally takes into consideration the memory and processing time limitations. The proposed method was evaluated on the real medical diagnosis task. The preliminary results of the experiments encourage us to continue works on the proposed approach.

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Notes

  1. 1.

    For so-called 0–1 loss function which returns 0 in the case of correct decision and 1 otherwise [8].

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Acknowlegements

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/). This work was also supported by the Polish National Science Center under the grant no. DEC-2013/09/B/ST6/02264. All computer experiments were carried out using computer equipment sponsored by ENGINE project.

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Authors and Affiliations

  1. Faculty of Electronics, Department of Systems and Computer Networks, Wrocław University of Science and Technology, Wrocław, Poland

    Michał Woźniak

  2. AGH University of Science and Technology, Kraków, Poland

    Bogusław Cyganek

  3. ENGINE Center, Wrocław University of Science and Technology, Wrocław, Poland

    Bogusław Cyganek

Authors
  1. Michał Woźniak
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  2. Bogusław Cyganek
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Corresponding author

Correspondence to Michał Woźniak .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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Woźniak, M., Cyganek, B. (2016). A First Attempt on Online Data Stream Classifier Using Context. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_50

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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