Title :
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
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;
Conference_Titel :
American Control Conference, 2008
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-2078-0
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2008.4587060
