基于决策属性支持度的知识约简方法

Knowledge Reduction Approach Based on Decision Attribute Support Degree

提出了一种基于决策属性支持度的属性相对约简算法·该算法利用粗糙集理论分析的方法,通过在知识表达系统中引入决策属性支持度的概念,来描述由条件属性所提供的知识对整体决策的支持程度,并通过决策属性支持度定义了条件属性对决策属性的相对重要性,以此作为启发式信息,可以方便地求出相对核·再以相对核作为求解最小相对约简的起点,按重要性的不同逐次选择重要属性添加到相对核中,直至其支持度达到整体条件属性支持度时为止,此时即得到知识库的最小约简·通过实例分析证明,该方法是有效的·

?A kind of attribute relative reduction for decision attribute support degree was proposed. With rough set theory and conception of decision attribute support degree applying in knowledge express system,the support degree of the knowledge supplied by the condition attribute for the whole decision was described and relative core was obtained using decision attribute support degress as heuristic information. Based on the relative core,attributes were selected one by one and inserted into relative core according to their importance degrees until the whole condition attribute support was met. This is the minimum reduction of knowledge database. The approach was effective in searching relative attribute reduction and relative core.