一种高效的不协调决策表约简算法  

An efficient attribute reduction algorithm in inconsistent decision tables

作　　者：李财莲[1] 滕书华[1] 孙即祥[1] 康耀红[2] 

机构地区：[1]国防科技大学电子科学与工程学院,湖南长沙410073 [2]海南大学信息科学技术学院,海南海口570228

出　　处：《国防科技大学学报》2013年第1期108-114,共7页Journal of National University of Defense Technology

基　　金：国家自然科学基金资助项目(40901216);中国博士后科学基金项目(2012M512168)

摘　　要：目前,不协调决策表的分布约简、最大分布约简和分配约简算法复杂度较高,不适合处理大数据集。在分析已有算法基础上,分析了基于相对可区分度的属性重要性度量的性质,解决了正域度量属性重要性的缺陷。针对不协调决策表,给出了多种简化协调决策表的定义,从而大大缩减了约简的实例数。以相对可区分度为启发函数构造了一种高效完备的不协调决策表约简算法。理论分析和实验结果表明,该约简算法解决了现有算法在复杂度和属性重要性度量上的缺陷,适合处理不协调的大数据集。Existing algorithms of distribution reduct, maximum distribution reduet and assignment reduct for inconsistent decision tables are inefficient, which are not suitable for large data sets. A measurement of attribute importance based on the relative discernibility degree was presented firstly, which overcomes the shortcoming of positive domain in measuring the importance of attributes. Then, in order to simplify the decision table, some kinds of simplified consistent decision tables were defined. In the end, an efficient attribute reduction algorithm was designed based on the relative discernibility degree. Theoretical analysis and experimental resuhs show the effectiveness and practicalbility of this algorithm on the large inconsistent data sets.

关 键 词：粗糙集 属性约简 不协调决策表 属性重要性 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]