Title :
Generalized probabilistic approximations
Author :
Grzyrnala-Busse, Jerzy W.
Author_Institution :
Electr. Eng. & Comput. Sci., Univ. of Kansas, Lawrence, KS, USA
Abstract :
Generalized probabilistic approximations, defined using both rough set theory and probability theory, are studied using an approximation space (U, R), where R is an arbitrary binary relation. Generalized probabilistic approximations are applicable in mining inconsistent data (data with conflicting cases) and data with missing attribute values.
Keywords :
approximation theory; data mining; probability; rough set theory; arbitrary binary relation; generalized probabilistic approximation space; inconsistent data mining; missing data attribute values; probability theory; rough set theory; Approximation algorithms; Approximation methods; Conferences; Data mining; Humidity; Probabilistic logic; Rough sets;
Conference_Titel :
Human System Interaction (HSI), 2013 The 6th International Conference on
Conference_Location :
Sopot
Print_ISBN :
978-1-4673-5635-0
DOI :
10.1109/HSI.2013.6577796
