Interpretability of support vector machines

Tamás Kenesei, J. Abonyi

Research output: Chapter

Abstract

Application of support vector methods for the initialization of fuzzy models is not a completely new idea. Numerous methods have been proposed to build the connection between the SVR and the FIS.

Original languageEnglish
Title of host publicationSpringerBriefs in Computer Science
PublisherSpringer
Pages49-60
Number of pages12
Edition9783319219417
DOIs
Publication statusPublished - jan. 1 2015

Publication series

NameSpringerBriefs in Computer Science
Number9783319219417
ISSN (Print)2191-5768
ISSN (Electronic)2191-5776

ASJC Scopus subject areas

  • Computer Science(all)

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  • Cite this

    Kenesei, T., & Abonyi, J. (2015). Interpretability of support vector machines. In SpringerBriefs in Computer Science (9783319219417 ed., pp. 49-60). (SpringerBriefs in Computer Science; No. 9783319219417). Springer. https://doi.org/10.1007/978-3-319-21942-4_4