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Jiménez Fernández, E.; Sánchez, A.; Sánchez Pérez, EA. (2022). Unsupervised machine learning approach for building composite indicators with fuzzy metrics. Expert Systems with Applications. 200:1-11. https://doi.org/10.1016/j.eswa.2022.116927
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/197967
Título: | Unsupervised machine learning approach for building composite indicators with fuzzy metrics | |
Autor: | Jiménez Fernández, E. Sánchez, A. | |
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[EN] This study aims at developing a new methodological approach for building composite indicators, focusingon the weight schemes through an unsupervised machine learning technique. The composite indicatorproposed is based ...[+]
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Derechos de uso: | Reconocimiento (by) | |
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Versión del editor: | https://doi.org/10.1016/j.eswa.2022.116927 | |
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This work was supported by the project FEDER-University of Granada (B-SEJ-242.UGR20), 2021-2023: An innovative methodological approach for measuring multidimensional poverty in Andalusia (COMPOSITE). Eduardo Jimenez-Fernandez ...[+]
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