Multiple Fuzzy Classification Systems

  • Rafał Scherer

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 288)

Table of contents

  1. Front Matter
    Pages 1-8
  2. Rafał Scherer
    Pages 1-5
  3. Rafał Scherer
    Pages 7-28
  4. Rafał Scherer
    Pages 29-37
  5. Rafał Scherer
    Pages 39-50
  6. Rafał Scherer
    Pages 51-59
  7. Rafał Scherer
    Pages 61-71
  8. Rafał Scherer
    Pages 73-79
  9. Back Matter
    Pages 0--1

About this book


Fuzzy classifiers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scientific and business applications. Fuzzy classifiers use fuzzy rules and do not require assumptions common to statistical classification. Rough set theory is useful when data sets are incomplete. It defines a formal approximation of crisp sets by providing the lower and the upper approximation of the original set. Systems based on rough sets have natural ability to work on such data and incomplete vectors do not have to be preprocessed before classification. To achieve better performance than existing machine learning systems, fuzzy classifiers and rough sets can be combined in ensembles. Such ensembles consist of a finite set of learning models, usually weak learners.

The present book discusses the three aforementioned fields – fuzzy systems, rough sets and ensemble techniques. As the trained ensemble should represent a single hypothesis, a lot of attention is placed on the possibility to combine fuzzy rules from fuzzy systems being members of classification ensemble. Furthermore, an emphasis is placed on ensembles that can work on incomplete data, thanks to rough set theory.


Boosting Classifiers Decision Making Ensemble Techniques Fuzzy Systems Mamdani Fuzzy Systems Negative Correlation Learning Neuro-Rough-Fuzzy Ensembles Pattern Recognition Takagi-Sugeno Fuzzy Systems

Authors and affiliations

  • Rafał Scherer
    • 1
  1. 1., Department of Computer EngineeringCzestochowa University of TechnologyCzestochowaPoland

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-30603-7
  • Online ISBN 978-3-642-30604-4
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site