Uriz Martín, Mikel XabierPaternain Dallo, DanielBustince Sola, HumbertoGalar Idoate, Mikel2020-04-172020-08-262019978-3-030-29859-310.1007/978-3-030-29859-3_31https://academica-e.unavarra.es/handle/2454/36749Trabajo presentado a la 14th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2019. León (España), 2019It is known that when dealing with interval-valued data, there exist problems associated with the non-existence of a total order. In this work we investigate a reformulation of an interval-valued decomposition strategy for multi-class problems called IVOVO, and we analyze the effectiveness of considering different admissible orders in the aggregation phase of IVOVO. We demonstrate that the choice of an appropriate admissible order allows the method to obtain significant differences in terms of accuracy.12 p.application/pdfeng© Springer Nature Switzerland AG 2019Multi-class classification problemsOne-vs-one strategyInterval-valued fuzzy setsAdmissible orderinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess