An efficient reduction algorithm of high-dimensional decision tables based on rough sets theory

After comparing several attribute significance reduction methods and analyzing the deep meanings and importance of indiscernibility relation defined by rough sets theory, according to the basic theory and the determining conditions on attribute reduction of RST, the paper brings forward the equivalence class maximum approximate match attribute significance reduction algorithm. Especially, the prophase reduction analysis plays a direct role in the reduction course. The availability and limited computation of the algorithm are proved by some examples and minimum reduction sets are obtained.