A fuzzy support vector machine with qualitative regression preset

Yicheng Wei, Junzo Watada, Witold Pedrycz

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    6 Citations (Scopus)

    Abstract

    In this paper, we formulate a qualitative classification model by means of qualitative fuzzy regression presetbased fuzzy support vector machine (FQR-FSVM). This new model will make it possible to achieve discrimination of output while characterizing membership for each class in terms of multi-dimensional qualitative inputs (attributes). Moreover, the new model will largely shorten the computing time especially for large database by using linear preset of fuzzy qualitative regression classifier to limit the non-linear classification region.

    Original languageEnglish
    Title of host publicationProceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012
    Pages393-399
    Number of pages7
    DOIs
    Publication statusPublished - 2012
    Event2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012 - Kitakyushu
    Duration: 2012 Aug 252012 Aug 28

    Other

    Other2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012
    CityKitakyushu
    Period12/8/2512/8/28

    Keywords

    • Fuzzy qualitative regression classifier
    • Fuzzy support vector machine (FSVM)
    • Qualitative classification

    ASJC Scopus subject areas

    • Biochemistry, Genetics and Molecular Biology(all)

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  • Cite this

    Wei, Y., Watada, J., & Pedrycz, W. (2012). A fuzzy support vector machine with qualitative regression preset. In Proceedings - 2012 6th International Conference on Genetic and Evolutionary Computing, ICGEC 2012 (pp. 393-399). [6457100] https://doi.org/10.1109/ICGEC.2012.15