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Applications of Soft Computing pp 305–314Cite as

Incremental Locally Linear Fuzzy Classifier

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 58))

Abstract

Optimizing the antecedent part of neuro-fuzzy system is investigated in a number of documents. Current approaches typically suffer from high computational complexity or lack of ability to extract knowledge from a given set of training data. In this paper, we introduce a novel incremental training algorithm for the class of neuro-fuzzy systems that are structured based on local linear classifiers. Linear discriminant analysis is utilized to transform the data into a space in which linear discriminancy of training samples is maximized. The neuro-fuzzy classifier is built in the transformed space, starting from the simplest form. In addition, rule consequent parameters are optimized using a local least square approach.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, K.N. Toosi University of Technology, P.O. Box 16315-1355, Tehran, Iran

    Armin Eftekhari, Mojtaba Ahmadieh Khanesar, Mohamad Forouzanfar & Mohammad Teshnehlab

Authors
  1. Armin Eftekhari
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  2. Mojtaba Ahmadieh Khanesar
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  3. Mohamad Forouzanfar
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  4. Mohammad Teshnehlab
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Editor information

Editors and Affiliations

  1. School of Applied Science (SAS) Decision Engineering Centre, Cranfield University , MK43 0AL, Cranfield, Bedfordshire, UK

    Jörn Mehnen  & Ashutosh Tiwari  & 

  2. Dept. of Artificial Intelligence Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology Kawazu , 820-8502, Iizuka, Fukuoka, Japan

    Mario Köppen

  3. Computer Science Department School of Computing, Armstrong Atlantic State University , 31419, Savannah, GA, USA

    Ashraf Saad

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© 2009 Springer-Verlag Berlin Heidelberg

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Eftekhari, A., Khanesar, M.A., Forouzanfar, M., Teshnehlab, M. (2009). Incremental Locally Linear Fuzzy Classifier. In: Mehnen, J., Köppen, M., Saad, A., Tiwari, A. (eds) Applications of Soft Computing. Advances in Intelligent and Soft Computing, vol 58. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89619-7_30

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  • DOI: https://doi.org/10.1007/978-3-540-89619-7_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89618-0

  • Online ISBN: 978-3-540-89619-7

  • eBook Packages: EngineeringEngineering (R0)

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