DocumentCode
498872
Title
Rough set model based on Sugeno measure
Author
Liu, Yao-Feng ; Tian, Da-Zeng ; Wang, Lin
Author_Institution
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding, China
Volume
3
fYear
2009
fDate
12-15 July 2009
Firstpage
1828
Lastpage
1833
Abstract
Probabilistic rough set model has a wide range of applications in uncertain information system. However, the probabilistic rough set model is based on the probability measure, which satisfies countable additivity. Considering the existence of many non-additive set functions in practical applications, rough set model based on the Sugeno measure is proposed. Moreover, the properties, the definition of roughness, together with the approximation accuracy of the proposed rough set model are provided.
Keywords
approximation theory; data analysis; probability; rough set theory; Sugeno measure; approximation accuracy; data analysis; probabilistic rough set model; uncertain information system; Application software; Cybernetics; Data analysis; Decision making; Electronic mail; Information systems; Machine learning; Mathematical model; Pattern recognition; Set theory; Lower- approximation; Rough set; Sugeno measure; Upper-approximation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3702-3
Electronic_ISBN
978-1-4244-3703-0
Type
conf
DOI
10.1109/ICMLC.2009.5212243
Filename
5212243
Link To Document