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

  • Athanasios Tsakonas
  • Bogdan Gabrys
Part of the Studies in Computational Intelligence book series (SCI, volume 577)

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.

Keywords

Support Vector Machine Genetic Programming Fuzzy Rule Multilayer Perceptrons Base Learner 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Athanasios Tsakonas
    • 1
  • Bogdan Gabrys
    • 1
  1. 1.Smart Technology Research CentreBournemouth UniversityFern BarrowU.K.

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