摘要
Reduction of attributes is one of important topics in the research on rough set theory. Wong S K M and Ziarko W have proved that finding the minimal attribute reduction of decision table is a NP-hard problem. Algorithm A (the improved algorithm to Jelonek) choices optimal candidate attribute by using approximation quality of single attribute,it improves efficiency of attribute reduction,but yet exists the main drawback that the single atribute having maximum approxiamtion quality is probably optimal candidate attribute. Therefore,in this paper, we introduce the concept of compatible decision rule,and propose an attribute reduction algorithm based on rules (ARABR). Algorithm ARABR provides a new method that measures the relevance between extending attribute and the set of present attributes, the method assures that the optimal attribute is extended, and obviously reduces the search space. Theory analysis shows that algorithm ARABR is of lower computational complexity than Jelonek's algorithm,and overcomes effectively the main drawback of algorithm A.
Reduction of attributes is one of important topics in the research on rough set theory. Wong S K M and Ziarko W have proved that finding the minimal attribute reduction of decision table is a NP-hard problem. Algorithm A (the improved algorithm to Jelonek) choices optimal candidate attribute by using approximation quality of single attribute, it improves efficiency of attribute reduction,but yet exists the main drawback that the single atribute having maximum approxiamtion quality is probably optimal candidate attribute. Thereforr, in this paper, we introduce the concept of compatible decision rule,and propose an attribute reduction algorithm based on rules (ARABR). Algorithm ARABR provides a new method that measures the relevance between extending attribute and the set of present attributes, the method assures that the optimal attribute is extended,and obviously reduces the search space. Theory analysis shows that algorithm ARABR is of lower computational complexity than Jelonek's algorithm,and overcomes effectively the main drawback of algorithm A.
出处
《计算机科学》
CSCD
北大核心
2003年第6期122-125,共4页
Computer Science
基金
国家自然科学基金(项目编号79970092)
安徽省教育厅自然科学研究基金资助(项目编号2001kj050)