k–Order Fuzzy Measures and k–Order Aggregation Functions

© 2020, Springer Nature Switzerland AG. This chapter studies simplifying assumptions on fuzzy measures that reduce the number of parameters required for their definition. In each case this is achieved by considering only subsets of up to cardinality k in one or another representation, leading to simplifications in their construction, learning and interpretation. However unlike the case of additive and symmetric fuzzy measures, this still leaves scope for modelling complex input interaction, a key benefit of using fuzzy measures.