Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society

The Application in Score Evaluation of Rought Set

Authors
Xueli Ren, Yubiao Dai
Corresponding Author
Xueli Ren
Available Online April 2016.
DOI
https://doi.org/10.2991/emim-16.2016.286How to use a DOI?
Keywords
Analogy; Score; Rough set ; Attribute Reduction; MAE
Abstract
A credit system is the need of higher education development. The grade management is the basis and core of the credit system. Therefore, it is necessary to estimate score as soon as possible. Estimation by analogy is a common method to estimate effort; it is used to estimate scores in the paper. As the courses are not as important in grade table, or even some courses are redundant to estimate score. Reducing the attribute of datasets is one of the core contents in rough set theory. It is applied in reducing the redundant course to improve the accuracy of estimation. Firstly, the equal width method is used to discrete data; then the redundant attributes are reduced by rough set; finally the reduce set is used to estimate score. An experiment is done to show the method feasible. The two methods of without reduction and with reduction are used to estimate scores; the results show that the mean absolution error of the method with reduction is smaller.
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Proceedings
6th International Conference on Electronic, Mechanical, Information and Management Society
Part of series
Advances in Computer Science Research
Publication Date
April 2016
ISBN
978-94-6252-176-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/emim-16.2016.286How 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  - Xueli Ren
AU  - Yubiao Dai
PY  - 2016/04
DA  - 2016/04
TI  - The Application in Score Evaluation of Rought Set
BT  - 6th International Conference on Electronic, Mechanical, Information and Management Society
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-16.2016.286
DO  - https://doi.org/10.2991/emim-16.2016.286
ID  - Ren2016/04
ER  -