Institutional Repository
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Preference disaggregation and statistical learning for multicriteria decision support: a review

Michael Doumpos, Zopounidis Konstantinos

Full record


URI: http://purl.tuc.gr/dl/dias/A96C320A-69BE-43E1-AAA7-580D6EAC61E1
Year 2011
Type of Item Peer-Reviewed Journal Publication
License
Details
Bibliographic Citation M. Doumpos and C. Zopounidis, "Preference disaggregation and statistical learning for multicriteria decision support: a review," Europ. J. Operat. Res., vol. 209, no. 3, pp. 203-214, Mar. 2011. doi:10.1016/j.ejor.2010.05.029 https://doi.org/10.1016/j.ejor.2010.05.029
Appears in Collections

Summary

Disaggregation methods have become popular in multicriteria decision aiding (MCDA) for eliciting preferential information and constructing decision models from decision examples. From a statistical point of view, data mining and machine learning are also involved with similar problems, mainly with regard to identifying patterns and extracting knowledge from data. Recent research has also focused on the introduction of specific domain knowledge in machine learning algorithms. Thus, the connections between disaggregation methods in MCDA and traditional machine learning tools are becoming stronger. In this paper the relationships between the two fields are explored. The differences and similarities between the two approaches are identified, and a review is given regarding the integration of the two fields.

Services

Statistics