Rough set theory ; a true landmark in data analysis
Along the years, rough set theory has earned a well-deserved reputation as a sound methodology for dealing with imperfect knowledge in a simple though mathematically sound way. This edited volume aims at continue stressing the benefits of applying rough sets in many real-life situations while still...
Guardat en:
| Altres autors: | , , , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2009. |
| Col·lecció: | Studies in Computational Intelligence
174 |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Rough set theory, a true landmark in data analysis, Ajith Abraham, Rafael Falcón, Rafael Bello (eds.), Berlin, Springer, 2009, 1 vol. (XV-322 p.), Studies in computational intelligence, 978-3-540-89920-4 • Rough Set Theory: A True Landmark in Data Analysis, Texte imprimé, 9783540899228 • Rough set theory, a true landmark in data analysis, Ajith Abraham, Rafael Falcón, Rafael Bello (eds.), Berlin, Springer, 2009, 1 vol. (XV-322 p.), Studies in computational intelligence, 978-3-540-89920-4 • Rough set theory, a true landmark in data analysis, Ajith Abraham, Rafael Falcón, Rafael Bello (eds.), Berlin, Springer, 2009, 1 vol. (XV-322 p.), Studies in computational intelligence, 978-3-540-89920-4 |
Taula de continguts:
- Theoretical Contributions to Rough Set Theory Rough Sets on Fuzzy Approximation Spaces and Intuitionistic Fuzzy Approximation Spaces Categorical Innovations for Rough Sets Granular Structures and Approximations in Rough Sets and Knowledge Spaces On Approximation of Classifications, Rough Equalities and Rough Equivalences Rough Set Data Mining Activities Rough Clustering with Partial Supervision A Generic Scheme for Generating Prediction Rules Using Rough Sets Rough Web Caching Software Defect Classification: A Comparative Study of Rough-Neuro-fuzzy Hybrid Approaches with Linear and Non-linear SVMs Rough Hybrid Models to Classification and Attribute Reduction Rough Sets and Evolutionary Computation to Solve the Feature Selection Problem Nature Inspired Population-Based Heuristics for Rough Set Reduction Developing a Knowledge-Based System Using Rough Set Theory and Genetic Algorithms for Substation Fault Diagnosis