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Interpretability Improvements to Find the Balance Interpretability-Accuracy in Fuzzy Modeling: An Overview

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Interpretability Issues in Fuzzy Modeling

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 128))

Abstract

Abstract System modeling with fuzzy rule-based systems (FRBSs), i.e. fuzzy modeling (FM), usually comes with two contradictory requirements in the obtained model: the interpretability, capability to express the behavior of the real system in an understandable way, and the accuracy, capability to faithfully represent the real system. While linguistic FM (mainly developed by linguistic FRBSs) is focused on the interpretability, precise FM (mainly developed by Takagi-Sugeno-Kang FRBSs) is focused on the accuracy. Since both criteria are of vital importance in system modeling, the balance between them has started to pay attention in the fuzzy community in the last few years.

The chapter analyzes mechanisms to find this balance by improving the interpretability in linguistic FM: selecting input variables, reducing the fuzzy rule set, using more descriptive expressions, or performing linguistic approximation; and in precise FM: reducing the fuzzy rule set, reducing the number of fuzzy sets, or exploiting the local description of the rules.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, E-18071, Granada, Spain

    Jorge Casillas, Oscar Cordón & Francisco Herrera

  2. Department of Mathematics Applied to Information Technologies, Technical University of Madrid, E-28040, Madrid, Spain

    Luis Magdalena

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  1. Dpto. Ciencias de la Computación e Inteligencia Artificial, Escuela Técnica Superior de Ingeniería Informática, Universidad de Granada, E - 18071, Granada, Spain

    Jorge Casillas , Oscar Cordón  & Francisco Herrera ,  & 

  2. Dpto. Matemáticas Aplicadas a las Tecnologías de la Información, Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, E - 28040, Madrid, Spain

    Luis Magdalena

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Casillas, J., Cordón, O., Herrera, F., Magdalena, L. (2003). Interpretability Improvements to Find the Balance Interpretability-Accuracy in Fuzzy Modeling: An Overview. In: Casillas, J., Cordón, O., Herrera, F., Magdalena, L. (eds) Interpretability Issues in Fuzzy Modeling. Studies in Fuzziness and Soft Computing, vol 128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37057-4_1

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