摘要
Rough集理论是一种新型的处理模糊性和不确定性知识的数学工具 ,正区域是该理论的核心概念之一 ,如何有效地计算正区域对提高各相关算法的性能至关重要 在对Rough集理论进行深入研究的基础上 ,提出且证明了一种新的快速计算正区域的方法 ,并进一步分析了正区域的渐增式计算 ,最后给出了详细的算法描述和时间复杂度分析 理论分析和实验结果表明 ,该方法能够有效地降低计算复杂度 。
Rough set theory is a new mathematical tool to deal with vagueness and uncertainty It has received considerable attention and has been applied in a variety of areas in recent years Positive region is one of the basic concepts in rough set theory How to compute positive region efficiently is very important for improving the performance of the relative algorithms Based on an in depth study of rough set theory, a new method for fast computing positive region is proposed and proved in this paper Furthermore, the incremental computing of positive region is analyzed Finally, the detailed descriptions of the algorithms are given In addition, their time complexities are analyzed respectively In order to test the efficiency of the algorithms, some experiments are made on the data sets in UCI (University of California, Irvine) machine learning repository The theoretical analysis and experimental results show that this new method can decrease the computational complexity effectively and it is much more efficient in comparison with those existing methods
出处
《计算机研究与发展》
EI
CSCD
北大核心
2003年第5期637-642,共6页
Journal of Computer Research and Development
基金
国家自然科学基金项目 (60 173 0 17
60 0 73 0 19
90 10 40 2 1)
北京市自然科学基金重点项目 (4 0 110 0 3 )
关键词
ROUGH集
下近似
正区域
约简
rough set
lower approximation
positive region
reduct
