Inconsistent Neighborhoods and Relevant Properties in Neighborhood Rough Set Models

DOI

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2016 International Conference on Computer Engineering and Information Systems
PB  - Atlantis Press
SP  - 149
EP  - 152
SN  - 2352-538X
UR  - https://doi.org/10.2991/ceis-16.2016.29
DO  - 10.2991/ceis-16.2016.29
ID  - Liao2016/11
ER  -