Algorithm for attribute relative reduction based on generalized binary discernibility matrix

Author

Zhang Tengfei ; Yang Xingxing ; Fumin Ma

Author_Institution

Coll. of Autom., Nanjing Univ. of Posts & Telecommun., Nanjing, China

fYear

2014

fDate

May 31 2014-June 2 2014

Firstpage

2626

Lastpage

2631

Abstract

The classical rough set theory, based on complete information system, can not directly deal with incomplete information system. This problem is solved to some extent by developing different kinds of extended rough set models. However, there is still not a unified definition for attributes relative reduction based on the extended rough set models. In this paper, a kind of generalized binary discernibility matrix for several typical extended rough set models was introduced, and a new algorithm for attribute relative reduction based on the generalized binary discernibility matrix was proposed. The feasibility of the proposed methods was demonstrated by the simulation and experiment analysis.

Keywords

data reduction; matrix algebra; rough set theory; attribute relative reduction; attributes relative reduction; classical rough set theory; extended rough set model; generalized binary discernibility matrix; information system; Algorithm design and analysis; Approximation methods; Ducts; Educational institutions; Information systems; Integrated circuit modeling; Set theory; Attribute Reduction; Generalized Binary Discernibility matrix; Incomplete Information System;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (2014 CCDC), The 26th Chinese

Conference_Location

Changsha

Print_ISBN

978-1-4799-3707-3

Type

conf

DOI

10.1109/CCDC.2014.6852617

Filename

6852617