Title :
An algorithm for attribute reduction of incomplete information system
Author_Institution :
Int. Port & Logistics Res. Center, Ningbo Univ. of Technol., Ningbo, China
Abstract :
By analyzing rough set model in incomplete information system, a binary discernibility matrix is introduced with constrained similarity relation. The method not only applies to the consistent incomplete information system, but also applies to the Inconsistent incomplete information system. And an algorithm is proposed for directly calculating attribute core and attribute relative reduction of incomplete information system, which is based on the under approximate binary discernibility matrix. The experiment shows that the algorithm is simple and efficient.
Keywords :
data mining; data reduction; information systems; rough set theory; attribute reduction; binary discernibility matrix; constrained similarity relation; incomplete information system; rough set model; Approximation methods; DVD; attribute reduction; binary discernibility matrix; constrained similarity relation; incomplete information;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658429
