Unsupervised machine learning approach for building composite indicators with fuzzy metrics
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Altres documents de l'autoria: Jiménez-Fernández, Eduardo; Sánchez Domínguez, Angeles; Sánchez Pérez, Enrique Alfonso
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Unsupervised machine learning approach for building composite indicators with fuzzy metricsData de publicació
2022-04-04Editor
ElsevierCita bibliogràfica
JIMÉNEZ-FERNÁNDEZ, E.; SÁNCHEZ, A.; PÉREZ, EA Sánchez. Unsupervised machine learning approach for building composite indicators with fuzzy metrics. Expert Systems with Applications, 2022, vol. 200, p. 116927.Tipus de document
info:eu-repo/semantics/articleVersió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
This study aims at developing a new methodological approach for building composite indicators, focusing on the weight schemes through an unsupervised machine learning technique. The composite indicator proposed is ... [+]
This study aims at developing a new methodological approach for building composite indicators, focusing on the weight schemes through an unsupervised machine learning technique. The composite indicator proposed is based on fuzzy metrics to capture multidimensional concepts that do not have boundaries, such as competitiveness, development, corruption or vulnerability. This methodology is designed for formative measurement models using a set of indicators measured on different scales (quantitative, ordinal and binary) and it is partially compensatory. Under a benchmarking approach, the single indicators are synthesized. The optimization method applied manages to remove the overlapping information provided for the single indicators, so that the composite indicator provides a more realistic and faithful approximation to the concept which would be studied. It has been quantitatively and qualitatively validated with a set of randomized databases covering extreme and usual cases. [-]
Publicat a
Expert Systems with Applications, Vol. 200, August 2022Entitat finançadora
FEDER-University of Granada | Universitat Jaume I | Universidad de Granada / CBUA
Codi del projecte o subvenció
B-SEJ-242.UGR20 | E-2018-03
Títol del projecte o subvenció
An innovative methodological approach for measuring multidimensional poverty in Andalusia (COMPOSITE)
Drets d'accés
© 2022 The Author(s). Published by Elsevier Ltd.
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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