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...
Call Number: | Libro Electrónico |
---|---|
Main Author: | |
Corporate Author: | |
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: | |
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.