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Experimental Study on Modified Radial-Based Oversampling

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International Joint Conference SOCO’18-CISIS’18-ICEUTE’18 (SOCO’18-CISIS’18-ICEUTE’18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 771))

Abstract

Although, imbalanced data analysis gained significant attention in the past years, it still remains an underdeveloped area of research posing many difficulties due to the difference in the number of objects in the examined classes, rendering traditional, accuracy driven machine learning methods useless. With many modern real-life applications being examples of imbalanced data classification i.e. fraud detection, medical diagnosis, oil-spills detection in satellite images or network anomaly detection, it is crucial to develop new algorithms suitable to use in such situations. One of the approaches to deal with the disproportion between the instances of objects in classes are either over- or undersampling techniques. In this paper, we propose a modification of an existing RBO algorithm. Due to the additional constraint the modified algorithm eliminates instances which may be problematic to classify. Additionally, a recursion mechanism was added in order to make the search of synthetic points more robust. The results obtained from computer experiments carried out on the benchmark datasets prove that the presented algorithm is applicable.

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Acknowledgements

This work is supported by the Polish National Science Center under the Grant no. UMO-2015/19/B/ST6/01597 as well the statutory funds of the Department of Systems and Computer Networks, Faculty of Electronics, Wrocław University of Science and Technology.

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Authors and Affiliations

  1. Faculty of Electronics, Department of Systems and Computer Networks, Wrocław University of Science and Technology, Wybrzee Wyspiańskiego 27, 50-370, Wrocław, Poland

    Barbara Bobowska & Michał Woźniak

Authors
  1. Barbara Bobowska
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  2. Michał Woźniak
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Corresponding author

Correspondence to Barbara Bobowska .

Editor information

Editors and Affiliations

  1. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    Manuel Graña

  2. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    José Manuel López-Guede

  3. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    Oier Etxaniz

  4. Department of Civil Engineering, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  5. University of Salamanca, Salamanca, Salamanca, Spain

    José Antonio Sáez

  6. Department of Industrial Engineering, University of A Coruña, La Coruña, La Coruña, Spain

    Héctor Quintián

  7. University of Salamanca, Salamanca, Salamanca, Spain

    Emilio Corchado

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Bobowska, B., Woźniak, M. (2019). Experimental Study on Modified Radial-Based Oversampling. In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_11

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