Proceedings of the 2016 International Conference on Computer Engineering and Information Systems

Inconsistent Neighborhoods and Relevant Properties in Neighborhood Rough Set Models

Authors
Shu-Jiao Liao, Qing-Xin Zhu, Rui Liang, Xin-Zheng Niu
Corresponding Author
Shu-Jiao Liao
Available Online November 2016.
DOI
https://doi.org/10.2991/ceis-16.2016.29How to use a DOI?
Keywords
Inconsistent neighborhood, rough set, lower and upper approximations, positive region, reduct.
Abstract
Rough set theory is an important branch of data mining and machine learning, among which neighborhood rough set is presented to deal with numerical data and hybrid data. In this paper, we propose a new concept called inconsistent neighborhood, and explore the relations between it and the existing notions in neighborhood rough set models. Some interesting properties are obtained accordingly. These properties can generate some new solutions to compute the quantities in neighborhood rough set, which are often more direct and more quick to obtain the results than the previous solutions.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2016 International Conference on Computer Engineering and Information Systems
Part of series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-283-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/ceis-16.2016.29How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shu-Jiao Liao
AU  - Qing-Xin Zhu
AU  - Rui Liang
AU  - Xin-Zheng Niu
PY  - 2016/11
DA  - 2016/11
TI  - Inconsistent Neighborhoods and Relevant Properties in Neighborhood Rough Set Models
BT  - 2016 International Conference on Computer Engineering and Information Systems
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/ceis-16.2016.29
DO  - https://doi.org/10.2991/ceis-16.2016.29
ID  - Liao2016/11
ER  -