摘要
Rough Set理论是处理不确定性知识、不完整数据的重要工具 ,在 Rough Set中属性最小约简与规则提取 NP-hard的 .本文针对现有属性约简与值约简算法的问题 ,分析了区分矩阵的特性 ,在此基础上 ,提出了属性与值约简的简化算法 ,并用实例作了验证 .
Rough Set theory, a important tool dealing with uncertainty and incomplete information, was introduced by Pawlak in 1982. Attribute reduction and value reduction are one of the key problems for the knowledge acquisition. Based on the rough set theory, the paper has made use of the characteristic of discernibility matrix and has presented a new attribute reduction and value reduction algorithm. The complexity of acquired rule knowledge can be reduced effectively in this way.
出处
《小型微型计算机系统》
CSCD
北大核心
2004年第2期245-247,共3页
Journal of Chinese Computer Systems
基金
国家自然基金项目 (6983 5 0 0 1)资助
山西省自然基金资助 (2 0 0 110 40 )
