Research on system uncertainty measures based on rough set theory

Authors:
Jun Zhao;Guoyin Wang
Affiliations:
Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China
Venue:
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Year:
2006

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Abstract

Due to various inherent uncertain factors, system uncertainty is an important intrinsic feature of decision information systems. It is important for data mining tasks to reasonably measure system uncertainty. Rough set theory is one of the most successful tools for measuring and handling uncertain information. Various methods based on rough set theory for measuring system uncertainty have been investigated. Their algebraic characteristics and quantitative relations are analyzed and disclosed in this paper. The results are helpful for selecting proper uncertainty measures or even developing new uncertainty measures for specific applications