【摘要】 <正> 1 引言波兰数学家Pawlak Z提出的Rough Set(RS,粗集)是一种新的处理不精确、不完全与不相容知识的数学方法。目前,它正在被广泛应用于人工智能、模式识别与智能信息处理等领域,并取得了一定的成果。属性约简是粗集理论及应用研究的重要内容之一,也是知识获取的关键步骤。属性约简作为粗集理论及应用研究的热点,备受研究者的关注。王珏等提出了基于差别矩阵的更多还原

【Abstract】 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.更多还原