Multiple Fuzzy Classification Systems

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 da...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Scherer, Rafał (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Edition:1st ed. 2012.
Series:Studies in Fuzziness and Soft Computing, 288
Subjects:
Computational intelligence.
Pattern recognition systems.
Computer simulation.
Computational Intelligence.
Automated Pattern Recognition.
Computer Modelling.
Online Access:Texto Completo
Table of Contents:
  • Introduction to fuzzy systems
  • Ensemble techniques
  • Relational modular fuzzy systems
  • Ensembles of the Mamdani fuzzy systems
  • Logical type fuzzy systems
  • Takagi-Sugeno fuzzy systems
  • Rough-neuro-fuzzy Ensembles for Classification with Missing Data
  • Concluding remarks and challenges for future research.

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