An Efficient Attribute Reduction Algorithm
Attribute reduction is one of the core contents in the theoretical research of rough sets. However, the inefficiency of attribute reduction algorithms limits the application of rough set. In this paper, we first point out some problems existing in the significance measure of attribute. Then a new measure, that is relative discernibility degree, is presented and proven to have the monotonicity property. Finally, a simplified consistent decision table is defined, based on which an efficient attribute reduction algorithm is designed. Theoretical analysis and experimental results show the effectiveness and practicalbility of this algorithm on the UCI data sets.
rough set distinguishability attribute reduction attribute importance
Shuhua Teng Jianwei Wu Jixiang Sun Shilin Zhou Gangqin Liu
College of Electronic Science & Engineering, National University of Defense Technology Changsha 4100 Modern Education Technology Center Luoyang Institute of Science and Technology Luoyang 471023 P.R.Ch
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
471-475
2010-03-27（万方平台首次上网日期，不代表论文的发表时间）