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Application of Base Learners as Conditional Input for Fuzzy Rule-Based Combined System

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Computational Intelligence (IJCCI 2012)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 577))

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Abstract

The aim of this work is to examine the possibility of using the output of base learners as antecedents for fuzzy rule-based hybrid ensembles. We select a flexible, grammar-driven framework for generating ensembles that combines multilayer perceptrons and support vector machines by means of genetic programming. We assess the proposed model in three real-world regression problems and we test it against multi-level, hierarchical ensembles. Our first results show that for a given large size of the base learners pool, the outputs of some of them can be useful in the antecedent parts to produce accurate ensembles, while at the same time other more accurate members of the same pool contribute in the consequent part.

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Authors and Affiliations

  1. Smart Technology Research Centre, Bournemouth University, Talbot Campus, Fern Barrow, Poole, BH12 5BB, U.K.

    Athanasios Tsakonas & Bogdan Gabrys

Authors
  1. Athanasios Tsakonas
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  2. Bogdan Gabrys
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Editor information

Editors and Affiliations

  1. University Paris-Est Créteil (UPEC), Créteil, France

    Kurosh Madani

  2. Departamento de Engenharia Informatica, University of Coimbra, Coimbra, Portugal

    António Dourado Correia

  3. Evolutionary Systems and Biomedical Engineering Lab, Instituto Superior Tecnico IST Systems and Robotics Institute, Lisboa, Portugal

    Agostinho Rosa

  4. Polytechnic Institute of Setúbal INSTICC, Setubal, Portugal

    Joaquim Filipe

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Tsakonas, A., Gabrys, B. (2015). Application of Base Learners as Conditional Input for Fuzzy Rule-Based Combined System. In: Madani, K., Correia, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2012. Studies in Computational Intelligence, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-11271-8_2

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  • DOI: https://doi.org/10.1007/978-3-319-11271-8_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11270-1

  • Online ISBN: 978-3-319-11271-8

  • eBook Packages: EngineeringEngineering (R0)

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