Refining CART Models for Covariate Shift with Importance Weight
Refining CART Models for Covariate Shift with Importance Weight
Machine learning models often face challenges in medical applications due to covariate shifts, where discrepancies between training and target data distributions can decrease predictive accuracy. This paper introduces an adaptation of Classification and Regression Trees (CART) that incorporates importance weighting to address these distributional differences effectively. By assigning greater weight …