Multiple Fuzzy Classification Systems
Fuzzy classi ers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scienti c and business applications. Fuzzy classi ers use fuzzy rules and do not require assumptions common to statistical classi cation. Rough set theory is useful when da...
Zapisane w:
| 1. autor: | |
|---|---|
| Format: | Livre numérique |
| Język: | Anglais |
| Wydane: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Seria: | Studies in Fuzziness and Soft Computing
288 |
| Dostęp online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme de l'éditeur (Springer) Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Komentarz: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Multiple Fuzzy Classification Systems, Texte imprimé, 9783642306037 • Multiple Fuzzy Classification Systems, Texte imprimé, 9783642436574 • Multiple Fuzzy Classification Systems, Texte imprimé, 9783642306051 |
Spis treści:
- 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.