Rough Set Based K-Exception Approach to Approximate Rule Reduction  

作　　者：ZHANG Feng ZHANG Xianfeng QIN Zhiguang LIU Jinde(School of Computer Science and Engineering University of Electronic Science and Technology of China,Sichuan,Chengdu 610054,P.R.China) 

出　　处：《Journal of Electronic Science and Technology of China》2003年第1期43-46,62,共5页中国电子科技（英文版）

摘　　要：There are rules refering to infrequent instances after the procession of attribute reductionand value reduction with traditional methods.A rough set RS based k-exception approach (RSKEA) torule reduction is presented.Its main idea lies in a two-phase RS based rule reduction.An ordinarydecision table is attained through general method of RS knowledge reduction in the first phase.Then a k-exception candidate set is nominated according to the decision table.RS rule reduction is employed forthe reformed source data set,which remove all the instances included in the k-exception set.We apply theapproach to the automobile database.Results show that it can reduce the number and complexity of ruleswith adjustable conflict rate,which contributes to approximate rule reduction.There are rules refering to infrequent instances after the procession of attribute reductionand value reduction with traditional methods.A rough set RS based k-exception approach (RSKEA) torule reduction is presented.Its main idea lies in a two-phase RS based rule reduction.An ordinarydecision table is attained through general method of RS knowledge reduction in the first phase.Then a k-exception candidate set is nominated according to the decision table.RS rule reduction is employed forthe reformed source data set,which remove all the instances included in the k-exception set.We apply theapproach to the automobile database.Results show that it can reduce the number and complexity of ruleswith adjustable conflict rate,which contributes to approximate rule reduction.

关 键 词：RULE EXCEPTION k-exception set approximate rule reduction 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]