Support Rough Sets for decision-making

DOI

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.

Copyright

© 2013, 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  - 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  - Proceedings of the 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  - 10.2991/.2013.11
ID  - Villuendas-Rey2013/10
ER  -