Authors
Chris Cornelis, Martine De Cock, Anna Maria Radzikowska
Publication date
2007
Conference
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing: 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings 11
Pages
87-94
Publisher
Springer Berlin Heidelberg
Description
The hybridization of rough sets and fuzzy sets has focused on creating an end product that extends both contributing computing paradigms in a conservative way. As a result, the hybrid theory inherits their respective strengths, but also exhibits some weaknesses. In particular, although they allow for gradual membership, fuzzy rough sets are still abrupt in a sense that adding or omitting a single element may drastically alter the outcome of the approximations. In this paper, we revisit the hybridization process by introducing vague quantifiers like “some” or “most” into the definition of upper and lower approximation. The resulting vaguely quantified rough set (VQRS) model is closely related to Ziarko’s variable precision rough set (VPRS) model.
Total citations
200820092010201120122013201420152016201720182019202020212022202320246591161114118614116101182
Scholar articles
C Cornelis, M De Cock, AM Radzikowska - Rough Sets, Fuzzy Sets, Data Mining and Granular …, 2007