摘要
决策表属性约简是粗集分析的重要内容 .最优属性约简是 NP困难问题 ,目前出现的启发式算法多是以决策表的核为起点 .但对于大型决策表 ,核一般计算量大 ,影响了整个算法的效率 .为此提出了一种分析决策表的属性约简算法 ,它不仅不依赖于核 ,反而为核提供了一种有效的计算方法 .其次 ,对人们容易忽略的含噪声决策表的属性约简也进行了分析 .
Feature reduct of decision tables is important for rough analysis. To consistent decision tables, the minimal reduct has been proved to be NP-hard. Many heuristic algorithms, therefore, have been given but most of them depend on the core of decision tables, which is not easy to get, especially for large-scale decision tables. In this way, there exist some problems such as efficiency and the solution completeness in them. Based on feature matrix put forward for reduct of decision tables, a new method to solve the difficulty is proposed in this paper. The method not only is independent of the core of decision tables, but provides a way-out for it. Also, decision tables containing null values, which are regardless and hard to deal with at present, are analyzed in depth in order to find useful information.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2003年第3期65-69,共5页
Systems Engineering-Theory & Practice
关键词
粗集
属性约简
启发式算法
决策表
空值
rough set
feature reduct
heuristic algorithm
decision table
null value
