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
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;
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
DOI :
10.1109/ICMLC.2009.5212243
