Basic Concepts in Covering-Based Rough Sets

Authors:
William Zhu
Affiliations:
The University of Auckland, New Zealand/ Chinese Academy of Sciences, China
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 05
Year:
2007

Citing 0
Cited 4

Relationship between generalized rough sets based on binary relation and covering

Information Sciences: an International Journal
On Covering Based Approximations of Classifications of Sets

IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
On some properties of covering based approximations of classifications of sets

Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Attribute reduction of data with error ranges and test costs

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Uncertainty and incompleteness of knowledge are widespread phenomena in information systems. Rough set theory is a tool for dealing with granularity and vagueness in data analysis. Rough set method has already been applied to various fields such as process control, economics, medical diagnosis, biochemistry, environmental science, biology, chemistry psychology, and conflict analysis. Covering-based rough set theory is an extension to classical rough sets. In this paper we study relationship between several basic concepts involved in covering-based rough sets. In this way we will have a better understanding of covering-based rough sets.