Matrix Aggregation Operators
Aggregation theory has traditionally focused on operators defined over vectors. However, many applications-including Multi-Criteria Decision Making, Group Decision Making, Fuzzy Rule-Based Classification Systems, and overlap/grouping indices-require aggregating information naturally structured as a matrix of membership degrees (e.g., where a set of objects interacts with a family of fuzzy sets). Despite this, no formal framework has been proposed for this class of operators, partly due to the common practice of flattening matrices into vectors (which discards structural information) and partly due to a reliance on decomposable operators that aggregate rows and columns sequentially. This p...
| Authors | Inmaculada Gutiérrez, Asier Urio-Larrea, J. Tinguaro Rodríguez et al. |
|---|---|
| Primary category | stat.ML |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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