Dependency space, closure system and rough set theory

被引：0

作者：

Xiangping Kang

Deyu Li

机构：

[1] Shanxi University,School of Computer and Information Technology

[2] Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education,undefined

来源：

International Journal of Machine Learning and Cybernetics | 2013年 / 4卷

关键词：

Rough set theory; Dependency space; Closure system;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper researches on potential relations of dependency space, closure system and rough set theory, and mainly focuses on solving some essential problems of rough set theory based on dependency space and closure system respectively. Firstly, we pretreat an information system into a relatively simple derivative system, in which dependency space and closure system are generated; Secondly, by means of dependency space and closure system separately we can solve some essential problems of rough set theory, such as reducts, cores; Finally, we reveal interior relations between dependency space and closure system. Conclusions of this paper not only help to understand rough set theory from the prospective of the dependency space and closure system, but also provide a new theoretical basis for data analysis and processing.

引用

页码：595 / 599

页数：4

共 50 条

[21] Rough set theory measures for quality assessment of a training set [J].

Caballero, Yaile ;

Bello, Rafael ;

Arco, Leticia ;

Marquez, Yennely ;

Leon, Pedro ;

Garcia, Maria M. ;

Casas, Gladys .

GRANULAR COMPUTING: AT THE JUNCTION OF ROUGH SETS AND FUZZY SETS, 2008, 224 :199-210

[22] Decision systems in rough set theory: A set operatorial perspective [J].

Chiaselotti, G. ;

Gentile, T. ;

Infusino, F. .

JOURNAL OF ALGEBRA AND ITS APPLICATIONS, 2019, 18 (01)

[23] Unsupervised Feature Selection Based on the Measures of Degree of Dependency using Rough Set Theory in Digital Mammogram Image Classification [J].

Velayutham, C. ;

Thangavel, K. .

2011 THIRD INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (ICOAC), 2011, :163-168

[24] Emphasis on Rough Set Theory for Image Retrieval [J].

Khodaskar, A. A. ;

Ladhake, S. A. .

2015 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI), 2015,

[25] Integrating rough set theory and medical applications [J].

Pattaraintakorn, Puntip ;

Cercone, Nick .

APPLIED MATHEMATICS LETTERS, 2008, 21 (04) :400-403

[26] ROUGH SET THEORY FOR SELECTING CLUSTERING ATTRIBUTE [J].

Herawan, Tutut ;

Dens, Mustafa Mat .

POWER CONTROL AND OPTIMIZATION, PROCEEDINGS, 2009, 1159 :331-338

[27] Neutrosophic fusion of rough set theory: An overview [J].

Zhang, Chao ;

Li, Deyu ;

Kang, Xiangping ;

Song, Dong ;

Sangaiah, Arun Kumar ;

Broumi, Said .

COMPUTERS IN INDUSTRY, 2020, 115

[28] Rough Set Theory and Its Extended Algorithms [J].

Andhalkar, Shital ;

Momin, B. F. .

PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS), 2018, :1434-1438

[29] A Review on Rough Set Theory in Medical Images [J].

Keerthana, R. Madhu ;

Jinila, Y. Bevish .

RESEARCH JOURNAL OF PHARMACEUTICAL BIOLOGICAL AND CHEMICAL SCIENCES, 2016, 7 (01) :815-822

[30] Supplier selection using rough set theory [J].

Chang, B. ;

Hung, H. F. ;

Lo, C. C. .

2007 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-4, 2007, :1461-+

← 1 2 3 4 5 →