Assessment of the influence of features on a classification problem: An application to COVID-19 patients
提出一种基于Shapley值的特征影响度量方法，并给出公理化刻画，通过实验验证其性能，最后应用于COVID-19患者数据，分析人口统计或风险因素对疾病进展的影响。
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.