摘要
在决策表中,为了评价某条件属性的重要性,不但要考虑这个属性(单一属性)相对于决策属性的重要性,还要考虑该条件属性与其他条件属性构成的属性集的重要性.在属性集依赖度比单一属性依赖度更加可信的事实基础上,提出了一个基于可分辨矩阵的属性集依赖度计算方法.该方法能够较快地获得可分辨矩阵,并直接求出属性集的依赖度,从而大大降低了算法的时间复杂度.实例验证了该方法具有较好的有效性和较低的时间复杂度.
In order to evaluate importance of one condition attribute, the importance of the condition attribute with respect to decision attribute and the attribute set which is composed of the condition attribute and others attributes must be simultaneously considered. A new importance degree evaluation method on attribute set is proposed based on discriminated matrix and the fact that dependency degree of attribute set is more authentic than dependency degree of single attribute. The proposed method can quickly get discriminated matrix and directly obtain dependency degree of attributes set. Examples show that it has better effectiveness and lower time complexity.
出处
《湖南师范大学自然科学学报》
CAS
北大核心
2013年第2期24-27,共4页
Journal of Natural Science of Hunan Normal University
基金
四川省科技厅应用基础研究重点资助项目(2011JY032)
阿坝师范高等专科学校校级重点科研资助项目(ASA11-26)
关键词
粗糙集
决策表
可分辨矩阵
依赖度
rough set
decision table
discriminated matrices
dependency degree
