On the influence of admissible orders in IVOVO
Fecha
2019Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión aceptada / Onetsi den bertsioa
Identificador del proyecto
ES/1PE/TIN2016-77356-P
Impacto
|
10.1007/978-3-030-29859-3_31
Resumen
It 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 ...
[++]
It 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. [--]
Materias
Multi-class classification problems,
One-vs-one strategy,
Interval-valued fuzzy sets,
Admissible order
Editor
Springer
Publicado en
Pérez García H., Sánchez González L., Castejón Limas M., Quintián Pardo H., Corchado Rodríguez E. (eds): Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science, vol 11734. Springer, Cham.
Notas
Trabajo presentado a la 14th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2019. León (España), 2019
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila /
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC
Versión del editor
Entidades Financiadoras
This work has been partially supported by the Spanish Ministry of Science and Technology under the project TIN2016-77356-P and the Public University of Navarre under the project PJUPNA13.