URI | http://purl.tuc.gr/dl/dias/BC4155A9-6DD1-4FFB-ABC8-620B28F0C858 | - |
Identifier | http://www.sciencedirect.com/science/article/pii/S0377221713010187 | - |
Identifier | https://doi.org/10.1016/j.ejor.2013.12.034 | - |
Language | en | - |
Extent | 11 pages | en |
Title | Inferring robust decision models in multicriteria classification problems: an experimental analysis | en |
Creator | Michael Doumpos | en |
Creator | Δουμπος Μιχαλης | el |
Creator | Zopounidis Konstantinos | en |
Creator | Ζοπουνιδης Κωνσταντινος | el |
Creator | Galariotis, Emilios | en |
Publisher | Elsevier | en |
Content Summary | Recent research on robust decision aiding has focused on identifying a range of recommendations from preferential information and the selection of representative models compatible with preferential constraints. This study presents an experimental analysis on the relationship between the results of a single decision model (additive value function) and the ones from the full set of compatible models in classification problems. Different optimization formulations for selecting a representative model are tested on artificially generated data sets with varying characteristics. | en |
Type of Item | Peer-Reviewed Journal Publication | en |
Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
License | http://creativecommons.org/licenses/by/4.0/ | en |
Date of Item | 2015-11-09 | - |
Date of Publication | 2014 | - |
Subject | Multiple criteria analysis | en |
Subject | Robustness | en |
Subject | Disaggregation analysis | en |
Subject | Monte Carlo simulation | en |
Bibliographic Citation | M. Doumpos, C. Zopounidis and E. Galariotis, "Inferring robust decision models in multicriteria classification problems: an experimental analysis," Europ. J. Operat. Res., vol. 236, no. 2, pp. 601-611, Jul. 2014. doi:10.1016/j.ejor.2013.12.034 | en |