Uncertainty measurement based on general relation

Author

Kong, Zhi ; Gao, Liqun ; Wang, Qingli ; Wang, Lifu ; Li, Yang

Author_Institution

Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang

fYear

2008

fDate

11-13 June 2008

Firstpage

3650

Lastpage

3653

Abstract

In incomplete information system, new information entropy and conditional entropy based on general relation are proposed. The results that the information entropy is extended from the general relation to equivalent relation and tolerance relation are found. Then the conclusion that the conditional entropy based on general relation decreases monotonously as the neighbor operators become finer is obtained. This paper presents some useful exploration about the incomplete information system from information views.

Keywords

data reduction; rough set theory; conditional entropy; equivalent relation; general relation; incomplete information system; information entropy; knowledge reduction; rough set theory; tolerance relation; uncertainty measurement; Data analysis; Information analysis; Information entropy; Information science; Information systems; Measurement uncertainty; Pattern analysis; Pattern recognition; Rough sets; Set theory; Conditional entropy; General relation; Incomplete information system; Information entropy; Rough set;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2008

Conference_Location

Seattle, WA

ISSN

0743-1619

Print_ISBN

978-1-4244-2078-0

Electronic_ISBN

0743-1619

Type

conf

DOI

10.1109/ACC.2008.4587060

Filename

4587060