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

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...

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Detalles Bibliográficos
Autores principales: Davila-Pena, Laura, García-Jurado, Ignacio, Casas-Méndez, Balbina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. 2022
Materias:
Analytics, Computational Intelligence and Information Management
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462009/
https://www.ncbi.nlm.nih.gov/pubmed/34584339
http://dx.doi.org/10.1016/j.ejor.2021.09.027
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author Davila-Pena, Laura
García-Jurado, Ignacio
Casas-Méndez, Balbina
author_facet Davila-Pena, Laura
García-Jurado, Ignacio
Casas-Méndez, Balbina
author_sort Davila-Pena, Laura
collection PubMed
description 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.
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spelling pubmed-84620092021-09-24 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 Eur J Oper Res Analytics, Computational Intelligence and Information Management 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. The Authors. Published by Elsevier B.V. 2022-06-01 2021-09-24 /pmc/articles/PMC8462009/ /pubmed/34584339 http://dx.doi.org/10.1016/j.ejor.2021.09.027 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Analytics, Computational Intelligence and Information Management
Davila-Pena, Laura
García-Jurado, Ignacio
Casas-Méndez, Balbina
Assessment of the influence of features on a classification problem: An application to COVID-19 patients
title Assessment of the influence of features on a classification problem: An application to COVID-19 patients
title_full Assessment of the influence of features on a classification problem: An application to COVID-19 patients
title_fullStr Assessment of the influence of features on a classification problem: An application to COVID-19 patients
title_full_unstemmed Assessment of the influence of features on a classification problem: An application to COVID-19 patients
title_short Assessment of the influence of features on a classification problem: An application to COVID-19 patients
title_sort assessment of the influence of features on a classification problem: an application to covid-19 patients
topic Analytics, Computational Intelligence and Information Management
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462009/
https://www.ncbi.nlm.nih.gov/pubmed/34584339
http://dx.doi.org/10.1016/j.ejor.2021.09.027
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