Evidential Clustering: A Review

Thierry Denoeux (1, 2, 3) , Orakanya Kanjanatarakul (4)

1 SU - Sorbonne Université
2 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
3 UTC - Université de Technologie de Compiègne
4 Faculty of Management Sciences, Chiang Mai Rajabhat University

In evidential clustering, uncertainty about the assignment of objects to clusters is represented by Dempster-Shafer mass functions. The resulting clustering structure, called a credal partition, is shown to be more general than hard, fuzzy, possibilistic and rough partitions, which are recovered as special cases. Three algorithms to generate a credal partition are reviewed. Each of these algorithms is shown to implement a decision-directed clustering strategy. Their relative merits are discussed.

Domaines: Intelligence artificielle [cs.AI]

Thierry Denoeux, Orakanya Kanjanatarakul. Evidential Clustering: A Review. 5th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2016), Nov 2016, Da Nang, Vietnam. pp.24-35, ⟨10.1007/978-3-319-49046-5_3⟩. ⟨hal-01397990⟩