Kernel Ridge Regression with Predicted Feature Inputs and Applications to Factor-Based Nonparametric Regression
带预测特征输入的核岭回归及其在因子型非参数回归中的应用
Kernel methods, particularly kernel ridge regression (KRR), are time-proven, powerful nonparametric regression techniques known for their rich capacity, analytical simplicity, and computational tractability. The analysis of their predictive performance has received continuous attention for more than two decades. However, in many modern regression problems where the feature inputs used in KRR cannot be directly observed and must instead be inferred from other measurements,…