一种基于分明矩阵的启发式知识约简方法  

Approach to heuristic knowledge reduction based on discernibility matrix

作　　者：陶志[1] 许宝栋[2] 汪定伟[2] 

机构地区：[1]中国民用航空学院理学院,天津300300 [2]东北大学信息科学与工程学院,辽宁沈阳110004

出　　处：《系统工程与电子技术》2005年第4期734-736,共3页Systems Engineering and Electronics

摘　　要：提出了基于分明矩阵的启发式知识约简方法。在决策表的相对约简过程中采用分明矩阵来表达知识,并利用分明矩阵中项的长度和每个属性的频率作为启发信息进行属性的选择。现已证明,寻找决策表中最小相对约简问题是典型的NP hard问题。所提供的算法在大多数情况下能够找到最小约简,即使在没找到最小约简的情况下,也能找到次优解。通过实例分析。An approach to heuristic knowledge reduction based on discernibility matrix is proposed. Knowledge is expressed first using discernibility matrix during the decision table's relative reduction and attributes are selected according to the elements' length in the discernibility matrix and the frequency of each attribute. It has been proved that the problem of searching minimum relative reduction is an NP hard problem. In the most cases the minimum reduction can be obtained using the proposed method. Otherwise, there must be a feasible solution. The practical results show that the approach is quick and effective in solving relative reduction problem.

关 键 词：粗糙集理论 决策表 相对约简 分明矩阵 属性加权频率 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]