Title :
An improved heuristic algorithm of attribute reduct in rough set
Author_Institution :
Dept. of Autom., Xiamen Univ., China
Abstract :
This paper introduces the background of rough set theory, and then brought forward a new algorithm for finding optimal reduct and make comparison between the original algorithm and the improved one via the experiment about the nine standard datasets in the UL database to explain the validity of the improved heuristic algorithm.
Keywords :
rough set theory; UL database; attribute reduct; improved heuristic algorithm; optimal reduct; rough set theory; Algorithm design and analysis; Automation; Data analysis; Databases; Heuristic algorithms; Information systems; Machine learning; Rough sets; Set theory; Standards development;
Conference_Titel :
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN :
0-7803-8653-1
DOI :
10.1109/ICARCV.2004.1468831
