变精度优势粗糙集属性约简择优算法

An Algorithm to Choose Reduction of Attributes of Variable Precision Dominance Rough Sets

以从多个粗糙集属性约简中选择最优的约简为目的,分析了作为度量工具的现有条件信息熵在应用过程中的缺陷.借鉴变精度粗糙集理论的思想,在对阈值参数进行二次选择的基础上,提出一种新的条件信息熵.基于新的条件信息熵设计了一种变精度优势粗糙集属性约简的择优算法,克服了现有条件信息熵的不足.理论分析和实践结果均表明了所设计算法的有效性.

The disadvantages of the current conditional information entropy are analyzed when conditional information entropy is used to measure reduction of attributes.Variable precision rough sets theory is used as a basis for proposing a new condition information,with another parameter chosen.Finally,a new algorithm is designed based on new conditional information entropy to choose reduction of attributes of ariable precision dominance rough.Theoretical analysis and experimental results show the effectiveness of the algorithm proposed.