On the learning of weights in some aggregation operators: the weighted mean and OWA operators
We study the determination of weights for two types of aggregation operators: the weighted mean and the OWA operator. We assume that there is at our disposal a set of examples for which the outcome of the aggregation operator is known. In the case of the OWA operator, we compare the results obtained...
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| Formato: | artículo |
| Fecha de publicación: | 1999 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/3557 |
| Acesso em linha: | https://hdl.handle.net/2099/3557 |
| Access Level: | acceso abierto |
| Palavra-chave: | Learning weigths Modelling Aggregation operators Weighted mean OWA operators WOWA operators Conjunts, Teoria de Classificació AMS::03 Mathematical logic and foundations::03E Set theory |
| Resumo: | We study the determination of weights for two types of aggregation operators: the weighted mean and the OWA operator. We assume that there is at our disposal a set of examples for which the outcome of the aggregation operator is known. In the case of the OWA operator, we compare the results obtained by our method with another one in the literature. We show that the optimal weighting vector is reached with less cost. |
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