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...
Clasificación: | Libro Electrónico |
---|---|
Autor principal: | Scherer, Rafał (Autor) |
Autor Corporativo: | SpringerLink (Online service) |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2012.
|
Edición: | 1st ed. 2012. |
Colección: | Studies in Fuzziness and Soft Computing,
288 |
Temas: | |
Acceso en línea: | Texto Completo |
Ejemplares similares
-
Fuzzy Evidence in Identification, Forecasting and Diagnosis
por: Rotshtein, Alexander P., et al.
Publicado: (2012) -
Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition
por: Melin, Patricia
Publicado: (2012) -
Computational Intelligence Paradigms in Advanced Pattern Classification
Publicado: (2012) -
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013
Publicado: (2013) -
Data Analysis and Pattern Recognition in Multiple Databases
por: Adhikari, Animesh, et al.
Publicado: (2014)