On the use of Valued Action Profiles for Relational Multicriteria Clustering CoDE-SMG – Technical Report Series
نویسندگان
چکیده
Data clustering techniques aim at eliciting hidden structures of a data set by partitioning it into groups of similar elements. In the case of relational clustering, the similarity is based on the relations that exist between elements rather than on intrinsic features of each element. However, applying relational clustering tools to the context of Multicriteria Decision Making requires caution due to the multicriteria nature of preference relations. This paper introduces the concept of Valued Action Profiles, a formalism for handling elements that are defined by pairwise valued outranking relations. These profiles are integrated into and studied on an adapted k-means algorithm that returns a relational partition. Experimental results on both artificial and real data sets show that the use of the proposed method leads to meaningful and robust relational partitions.
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