Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)

An Approach for Attribute Weights Acquisition based on Rough Sets Theory and Information Gain

Authors
Dun Liu1, Pei Hu, Tianrui Li, Chaozhe Jiang
1School of Economics and Management, Southwest Jiaotong University
Corresponding Author
Dun Liu
Available Online October 2007.
DOI
10.2991/iske.2007.33How to use a DOI?
Keywords
Rough sets theory, information gain, attributes reduct, weight.
Abstract

The irrationality of constructing weights, lending to subjectivity and without considering the redundancy of attributes, exists in traditional management decision-making. The important rating and important rating are first proposed by the attribute reduct in rough sets theory. Then, the important rating is given by the information gain in information entropy. An approach for acquiring attribute weights employing the three important ratings is presented to solve the problem of subjectivity and redundancy. An empirical case study validates the rationality and validity of our method

Copyright
© 2007, 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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Volume Title
Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
Series
Advances in Intelligent Systems Research
Publication Date
October 2007
ISBN
978-90-78677-04-8
ISSN
1951-6851
DOI
10.2991/iske.2007.33How to use a DOI?
Copyright
© 2007, 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/).

Cite this article

TY  - CONF
AU  - Dun Liu
AU  - Pei Hu
AU  - Tianrui Li
AU  - Chaozhe Jiang
PY  - 2007/10
DA  - 2007/10
TI  - An Approach for Attribute Weights Acquisition based on Rough Sets Theory and Information Gain
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 188
EP  - 194
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.33
DO  - 10.2991/iske.2007.33
ID  - Liu2007/10
ER  -