A heuristic algorithm for attribute reduction in incomplete information systems

被引：0
|
作者：
Li, F [1 ]
Liu, QH [1 ]
Yang, GW [1 ]
机构：
[1] Univ Elect Sci & Technol China, Coll Comp Sci & Engn, Chengdu 610054, Peoples R China
来源：
Progress in Intelligence Computation & Applications | 2005年
关键词：
rough set theory; attribute reduction; incomplete information systems;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The rough set theory is a novel mathematical approach to uncertainty and vague data analysis. In practice, information systems are incomplete frequently, which means the classical rough set theory needs,to be extended. In this paper, based on the analysis of the properties related to attribute reduction in the tolerance-relation-based rough set theory, the. significance of each attribute is proposed. Using it as heuristic information, a complete algorithm for attribute reduction is proposed. In addition, the complexity of the algorithm is analyzed in detail. Experimental results show that this algorithm is efficient in finding a minimal reduct.
引用
收藏
页码：574 / 580
页数：7
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