摘要
扩展了Rough集正区域和边界的定义,在得到信息系统最大正区域的前提下,给出了认知正区域、认知属性核和认知属性约简的定义,并给出了从经典属性约简到认知属性约简转换的高效算法。此外,在认知正区域的定义下,由于决策表的不相容性,在变精度模型下实现属性约简的增量处理是相当困难的,结合提出的高效算法,解决了这一问题。最后,仿真实验说明了算法的有效性。
The definitions of cognitive positive region,cognitive attribute core and cognitive attribute reduction are proposed,by extending the notions of positive region and boundary region in classic rough set theory.Furtherrnore,a high efficient algorithm of transforming classic attribute reduction to cognitive attribute reduction is presented.It is difficult to implement incremental attribute reduction in VPRS model due to the non-tolerance of decision table,which is solved by combining high efficient transforming algorithm.Experimental results illuminate the validity and effectiveness of algorithms.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第34期145-148,共4页
Computer Engineering and Applications
关键词
粗集
决策表
认知核属性
认知属性约简
增量式
rough set
decision table
cognitive core attribute
cognitive attribute reduction
incremental
