RT Journal Article
T1 Assessment of the influence of features on a classification problem: an application to COVID-19 patients
A1 Davila Pena, Laura
A1 García Jurado, Ignacio
A1 Casas Méndez, Balbina
K1 Machine learning
K1 Classification
K1 Influence of features
K1 Shapley value
K1 COVID-19
AB This paper deals with an important subject in classification problems addressed by machine learning techniques: the evaluation of the influence of each of the features on the classification of individuals. Specifically, a measure of that influence is introduced using the Shapley value of cooperative games. In addition, an axiomatic characterisation of the proposed measure is provided based on properties of efficiency and balanced contributions. Furthermore, some experiments have been designed in order to validate the appropriate performance of such measure. Finally, the methodology introduced is applied to a sample of COVID-19 patients to study the influence of certain demographic or risk factors on various events of interest related to the evolution of the disease
PB Elsevier
YR 2022
FD 2022
LK http://hdl.handle.net/10347/27677
UL http://hdl.handle.net/10347/27677
LA eng
NO European Journal of Operational Research 299 (2022) 631-641. https://doi.org/10.1016/j.ejor.2021.09.027
NO The authors are grateful to Ricardo Cao Abad and to the Dirección Xeral de Saúde Pública of the Xunta de Galicia in Spain. This work has been supported by the ERDF, the Government of Spain/AEI [grants MTM2017-87197-C3-1-P and MTM2017-87197-C3-3-P]; the Xunta de Galicia [Grupos de Referencia Competitiva ED431C2016-015, ED431C2017/38, and ED431C 2021/24, and Centro Singular de Investigación de Galicia ED431G/01]; and by the collaborative research project of the IMAT “Mathematical, statistical and dynamic study of the epidemic COVID-19”, subsidized by the Vice-Rector’s Office for Research and Innovation at the University of Santiago de Compostela, Spain. The research of Laura Davila-Pena has been funded by the Government of Spain [grant FPU17/02126]. We would also like to thank the three anonymous referees and the editor for their constructive comments and suggestions, which helped us to improve the final version of this paper
DS Minerva
RD 24 abr 2026