Algorithm for Extracting All Relative-Attribute Reducts in Decision System of Large-Scale Records

作     者：张国军 高超 ZHANG Guo-jun GAO Chao 1.School of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan 430070,China2.Huangshi Institute of Technology,Huangshi 435000,China

作者机构：School of Computer Science and TechnologyHuazhong University of Science and Technology Huangshi Institute of Technology 

出 版 物：《Journal of Southwest Jiaotong University(English Edition)》 (西南交通大学学报（英文版）)

年 卷 期：2010年第18卷第2期

页      面：166-170页

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Rough set Relative-attribute reducts Large-scale records 

摘      要：A new algorithm based on rough core was proposed to extract all relative-attribute reducts in decision information systems of large-scale records. In the algorithm, the rough core of the decision-making information system is first calculated. Then, an approach based on a top-down strategy is adopted to select the non-core condition attributes and generate candidate relative-attribute reducts. Finally, the set of all relative-attribute reducts is obtained by pruning the candidate relative-attribute reducts. Experimental results show that the proposed algorithm is superior to the other methods such as the algorithm without computing core, the exhaustive method and the discernibility matrix method in extracting all relative-attribute reducts for large-scale data sets.