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

Laura Davila-Pena; Ignacio García-Jurado; Balbina Casas-Méndez

doi:10.1016/j.ejor.2021.09.027

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

Eur J Oper Res. 2022 Jun 1;299(2):631-641. doi: 10.1016/j.ejor.2021.09.027. Epub 2021 Sep 24.

Authors

Laura Davila-Pena¹, Ignacio García-Jurado², Balbina Casas-Méndez¹

Affiliations

¹ MODESTYA Research Group, Department of Statistics, Mathematical Analysis and Optimisation and IMAT, Faculty of Mathematics, University of Santiago de Compostela, Campus Vida, Santiago de Compostela 15782, Spain.
² MODES Research Group, Department of Mathematics and CITIC, Faculty of Computer Science, University of A Coruña, Campus de Elviña, A Coruña 15071, Spain.

Abstract

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.

Keywords: COVID-19; Classification; Influence of features; Machine learning; Shapley value.