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Case Study: Interpretability of Fuzzy Systems Applied to Identity Verification

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Book cover Design of Interpretable Fuzzy Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 684))

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Abstract

In Sect. 2.2 and Chaps. 5–7 we present typical schemes of fuzzy system learning, which can be used, for example, in the case when we do not have expert knowledge but we have learning data. In practice, solutions are also used in which an expert initially determines the number of rules and approximate distribution of fuzzy sets with the aim of a learning process being the fine tuning of a fuzzy system.

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Authors and Affiliations

  1. Institute of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland

    Krzysztof Cpałka

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  1. Krzysztof Cpałka
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Correspondence to Krzysztof Cpałka .

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Cpałka, K. (2017). Case Study: Interpretability of Fuzzy Systems Applied to Identity Verification. In: Design of Interpretable Fuzzy Systems. Studies in Computational Intelligence, vol 684. Springer, Cham. https://doi.org/10.1007/978-3-319-52881-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-52881-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52880-9

  • Online ISBN: 978-3-319-52881-6

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