Uncertainty measures of roughness of knowledge and rough sets in incomplete information systems

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Abstract

In this paper we address uncertainty measures of roughness of knowledge and rough sets by introducing rough entropy in incomplete information systems. We make only one assumption about unknown values: the real value of a missing attribute is one from the attribute domain. However, we do not assume which one. We prove that the rough entropy of knowledge and the rough entropy of rough sets decrease monotonously as the granularity of information smaller through finer partitionings.These conclusions are helpful people to understand the essence of rough set theory and essential to seek new efficient algorithm of knowledge reduction in incomplete information systems.

Original languageEnglish
Pages2526-2529
Number of pages4
StatePublished - 2000
EventProceedings of the 3th World Congress on Intelligent Control and Automation - Hefei, China
Duration: 28 Jun 20002 Jul 2000

Conference

ConferenceProceedings of the 3th World Congress on Intelligent Control and Automation
Country/TerritoryChina
CityHefei
Period28/06/002/07/00

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