Interpretability of support vector machines

Tamás Kenesei, J. Abonyi

Research output: Chapter in Book/Report/Conference proceedingChapter

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

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Support vector machines

ASJC Scopus subject areas

  • Computer Science(all)

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

Interpretability of support vector machines. / Kenesei, Tamás; Abonyi, J.

SpringerBriefs in Computer Science. 9783319219417. ed. Springer, 2015. p. 49-60 (SpringerBriefs in Computer Science; No. 9783319219417).

Research output: Chapter in Book/Report/Conference proceedingChapter

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