Parallel reducts based on attribute significance

Authors:
Dayong Deng;Dianxun Yan;Jiyi Wang
Affiliations:
Xingzhi College, Zhejiang Normal University, Jinhua, China and College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China;College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China;College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China
Venue:
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Year:
2010

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Abstract

In the paper, we focus on how to get parallel reducts. We present a new method based on matrix of attribute significance, by which we can get parallel reduct as well as dynamic reduct. We prove the validity of our method in theory. The time complex of our method is polynomial. Experiments show that our method has advantages of dynamic reducts.