Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support

Support Rough Sets for decision-making

Authors
Yenny Villuendas-Rey, Maria M. Garcia-Lorenzo, Rafael Bello
Corresponding Author
Yenny Villuendas-Rey
Available Online October 2013.
DOI
https://doi.org/10.2991/.2013.11How to use a DOI?
Keywords
Case based decision-making, Rough Set Theory, data preprocessing
Abstract
Case-based reduction is viewed as an important prepro-cessing step for case based decision-making. In this pa-per, is introduced a Support Rough Set model to deal with mixed and incomplete data. The Support Rough Set mod-el is used to reduce the case base by using positive and limit regions of decision. The proposed algorithms are compared with some classical techniques. Experimental results show that the proposed methods obtain high accu-racy, using only a reduced case base.
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Proceedings
Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2013
ISBN
978-90-78677-86-4
ISSN
1951-6851
DOI
https://doi.org/10.2991/.2013.11How 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  - Yenny Villuendas-Rey
AU  - Maria M. Garcia-Lorenzo
AU  - Rafael Bello
PY  - 2013/10
DA  - 2013/10
TI  - Support Rough Sets for decision-making
BT  - Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
PB  - Atlantis Press
SP  - 88
EP  - 97
SN  - 1951-6851
UR  - https://doi.org/10.2991/.2013.11
DO  - https://doi.org/10.2991/.2013.11
ID  - Villuendas-Rey2013/10
ER  -