太原理工大学学报2017，Vol.48Issue(5)：822-827,6.DOI:10.16355/j.cnki.issn1007-9432tyut.2017.05.021
基于变精度粗糙集的多粒度最简规则获取方法
A Method of Multi-granularity Concise Rules Acquisition Based on Variable Precision Rough Set Models
摘要
Abstract
Traditional algorithm extraction rules by attribute reduction and attribute values re-duction.There is a lot of redundant computation in the process and the result is not good when the data contains noise.Thus,the variable precision rough set model is used to acquire the rules of decision and attribute reduction and value reduction process are combined in this paper.The decision table is granulated into different granular spaces from fine to coarse in the perspective of attribute multi-granulation.By defining granular matrix,βgranular relation matrix,as well as mining the heuristic information Sωhidden in theβmatrices to determine the order of attribute re-duction,the rules in different granular space are acquired.By defining the concept of coverageα, the convergence speed of the algorithm is accelerated by the method of probability.Finally,the proposed algorithm is illustrated by an example and verified by UCI test set,proving the validity and effectiveness of the proposed algorithm.关键词
规则获取/变精度粗糙集/粒计算/多粒度Key words
rule acquisition/variable precision rough set/granular computing/multi-granulation分类
信息技术与安全科学引用本文复制引用
尚晓慧,闫继雄,陈泽华..基于变精度粗糙集的多粒度最简规则获取方法[J].太原理工大学学报,2017,48(5):822-827,6.基金项目
国家自然科学基金项目资助(61402319) （61402319）
山西省回国留学人员科研项目资助(2013-031) （2013-031）
