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On Speeding Up the Learning Process of Neuro-fuzzy Ensembles Generated by the Adaboost Algorithm

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Computer Recognition Systems 2

Part of the book series: Advances in Soft Computing ((AINSC,volume 45))

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Abstract

Boosting is one of the most popular methods of multiple classification. In the paper we propose a method for speeding up the learning process by modifying the backpropagation algorithm and fuzzy clustering algorithm for boosting learning of several neuro-fuzzy classifiers. Simulations show superior performance of our method comparing to a standard boosting classification.

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© 2007 Springer-Verlag Berlin Heidelberg

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Korytkowski, M., Rutkowski, L., Scherer, R. (2007). On Speeding Up the Learning Process of Neuro-fuzzy Ensembles Generated by the Adaboost Algorithm. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_40

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  • DOI: https://doi.org/10.1007/978-3-540-75175-5_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75174-8

  • Online ISBN: 978-3-540-75175-5

  • eBook Packages: EngineeringEngineering (R0)

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