Name
Abstract | ||
|---|---|---|
In this paper, within the context of fuzzy rough set theory, we generalize the classical rough set framework for data-based attribute selection and reduction, based on the notion of fuzzy decision reducts. Experimental analysis confirms the potential of the approach. |
Year | Venue | Keywords |
|---|---|---|
2008 | RSKT | feature selection,data-based attribute selection,experimental analysis,fuzzy rough set theory,fuzzy decision reducts,classical rough set framework,rough set,classification,rough set theory,rough sets,fuzzy set,fuzzy sets,attribute selection |
Field | DocType | Volume |
Data mining,Fuzzy classification,Computer science,Fuzzy set operations,Fuzzy mathematics,Fuzzy set,Artificial intelligence,Fuzzy number,Dominance-based rough set approach,Pattern recognition,Rough set,Type-2 fuzzy sets and systems,Machine learning | Conference | 5009 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-79720-3 | 19 |
PageRank | References | Authors |
0.95 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chris Cornelis | 1 | 2116 | 113.39 |
| Germán Hurtado Martín | 2 | 153 | 5.40 |
| Richard Jensen | 3 | 1924 | 76.18 |
| Dominik Ślęzak | 4 | 553 | 50.04 |