Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling
通过 CATE 建模与 Shapley 值识别预测性生物标志物:概述与实践建议
In recent years, two parallel research trends have emerged in machine learning, yet their intersections remain largely unexplored. On one hand, there has been a significant increase in literature focused on Individual Treatment Effect (ITE) modeling, particularly targeting the Conditional Average Treatment Effect (CATE) using meta-learner techniques. These approaches often aim to identify causal effects from observational data. On the other hand, the field of Explainable…