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IFIP International Conference on Computer Information Systems and Industrial Management

CISIM 2018: Computer Information Systems and Industrial Management pp 254–265Cite as

Parallel C–Fuzzy Random Forest

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11127))

Abstract

The C–fuzzy random forest is a novel ensemble classifier which uses C-fuzzy decision trees as unit classifiers. The main problem connected with this classifier is a relatively long learning process time. In this paper the method of reducing the C–fuzzy random forest’s learning time is proposed. Authors proposed and described the method of parallelization of this classifier’s learning process by generating trees which are the parts of the forest in separate threads. The experiments which were designed to check the effectiveness of the proposed method were performed and the results were presented and discussed.

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Notes

  1. 1.

    There is also another decision–making strategy which assumes making the single decision by the whole forest. It is described in [2].

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Acknowledgment

This work was supported by the grant S/WI/3/2018 from Bialystok University of Technology founded by Ministry of Science and Higher Education.

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Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Wiejska 45A, 15-351, Bialystok, Poland

    Łukasz Gadomer & Zenon A. Sosnowski

Authors
  1. Łukasz Gadomer
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  2. Zenon A. Sosnowski
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Corresponding authors

Correspondence to Łukasz Gadomer or Zenon A. Sosnowski .

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Editors and Affiliations

  1. Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

  2. Warsaw University of Technology, Warsaw, Poland

    Władysław Homenda

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Gadomer, Ł., Sosnowski, Z.A. (2018). Parallel C–Fuzzy Random Forest. In: Saeed, K., Homenda, W. (eds) Computer Information Systems and Industrial Management. CISIM 2018. Lecture Notes in Computer Science(), vol 11127. Springer, Cham. https://doi.org/10.1007/978-3-319-99954-8_22

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  • DOI: https://doi.org/10.1007/978-3-319-99954-8_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99953-1

  • Online ISBN: 978-3-319-99954-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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