自动化学报2012，Vol.38Issue(11)：1751-1756,6.DOI:10.3724/SP.J.1004.2012.01751
高可信度最小约简属性启发策略
High Confidence Heuristic Strategy for Minimal Reduction
摘要
Abstract
In order to improve the confidence of minimal reducts calculated by heuristic methods, some important characters of attributes, such as absorption, repulsion, and mutex etc., are presented based on the discernibility matrix. Then the related heuristic strategies are proposed by analyzing the relation between these characters and the minimal reducts. Some confidence models of these strategies are established to order these strategies. On the basis, an integrated strategy and a related reduction algorithm are proposed to calculate a minimal redcut. Theoretic and experimental analyses show that the proposed strategies are of high confidence and effectiveness.关键词
属性吸收/属性排斥/属性互斥/最小约简/可信度Key words
Attribute absorption/ attribute repulsion/ attribute mutex/ minimal reduct/ confidence引用本文复制引用
尹林子,李勇刚,阳春华,桂卫华..高可信度最小约简属性启发策略[J].自动化学报,2012,38(11):1751-1756,6.基金项目
国家自然科学基金(60874069,60904077),国家杰出青年科学基金(61025015)资助 （60874069,60904077）
