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Assessment of the influence of features on a classification problem: An application to COVID-19 patients

Davila-Pena, Laura, García-Jurado, Ignacio, Casas-Méndez, Balbina (2022) Assessment of the influence of features on a classification problem: An application to COVID-19 patients. European Journal of Operational Research, 299 (2). pp. 631-641. ISSN 0377-2217. E-ISSN 1872-6860. (doi:10.1016/j.ejor.2021.09.027) (KAR id:103928)


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.

Item Type: Article
DOI/Identification number: 10.1016/j.ejor.2021.09.027
Uncontrolled keywords: Machine learning; Classification; Influence of features; Shapley value; COVID-19
Subjects: Q Science
Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > Operations Research - Theory
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Funders: Xunta de Galicia (
Government of Spain (
Depositing User: Laura Davila Pena
Date Deposited: 05 Feb 2024 13:59 UTC
Last Modified: 06 Feb 2024 21:52 UTC
Resource URI: (The current URI for this page, for reference purposes)

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