On the use of valued action profiles for relational multi-criteria clustering

Stefan Eppe, Julien Roland and Yves De Smet

International Journal of Multicriteria Decision Making, 2014, vol. 4, issue 3, 201-233

Abstract: Clustering techniques aim at eliciting hidden structures of a dataset by partitioning it into groups of similar elements. We will focus on the special case of relational clustering, where the similarity is based on relations that exist between elements rather than on their respective intrinsic features. As will be shown, particular attention has to be paid when applying a relational approach to the context of multi-criteria decision making. This paper introduces the concept of valued action profiles, a formalism for handling elements that are defined by pairwise valued outranking relations. For our experimental study, we then integrate these profiles into an adapted k-means algorithm that returns a relational partition. Results on both artificial and real datasets show that the use of the proposed method leads to meaningful relational partitions.

Keywords: multiple criteria analysis; relational clustering; action profiles; outranking relations; fuzzy relations; MCDM; multicriteria decision making; fuzzy logic; pairwise comparison; valued outranking relations; adapted k-means algorithm; artificial datasets; real datasets; relational partitions. (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.inderscience.com/link.php?id=64796 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmcdm:v:4:y:2014:i:3:p:201-233

Access Statistics for this article

More articles in International Journal of Multicriteria Decision Making from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().