Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6897437 | European Journal of Operational Research | 2014 | 27 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Michael Doumpos, Constantin Zopounidis, Emilios Galariotis,