连续值属性决策表中的可变精度粗糙集模型及属性约简  

Attributes Reduction Based on the Variable Precision Rough Set in Decision Tables Containing Continuous-valued Attributes

作　　者：冯林[1,2] 李天瑞[2] 余志强[3] 

机构地区：[1]四川师范大学计算机科学学院,成都610101 [2]西南交通大学信息科学与技术学院,成都610031 [3]成都飞机工业(集团)有限责任公司,成都610092

出　　处：《计算机科学》2010年第9期205-208,共4页Computer Science

基　　金：国家自然科学基金(No.60873108);四川省教育厅科研基金(No.09ZC079);四川师范大学重点研究课题资助

摘　　要：属性约简是粗糙集理论研究的一个核心问题。为了有效地处理决策表中连续值属性约简,提出了连续值属性决策表中的可变精度粗糙集模型以及基于此模型的连续值属性约简算法。仿真实验结果表明,该算法可以对连续值属性进行约简,而且比经典粗糙集相关方法在处理连续值属性约简方面更有效。Attribute reduction is one of the key problems of the rough set theory.In order to effectively use the rough set theory to deal with the problem of attribute reduction in Decision Tables containing Continuous-Valued Attributes（DTCVA） directly,a new variable precision rough set model and a heuristic algorithm for attributes reduction in DTCVA were developed.Simulation results show that the proposed approach is effective for reduction of continuous-valued attributes,and more efficient than the classical rough set approaches in processing attribute reduction in decision information systems containing continuous-valued attributes.

关 键 词：粗糙集 属性约简 可变精度粗糙集 属性重要性 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]