Background: The Importance of Variable Selection in Machine Learning Regression Models In recent years, the widespread application of machine learning in the fields of bioinformatics and data science has greatly driven the development of predictive modeling. Random forest (RF) regression, as a commonly used ensemble learning algorithm, has become a...

Research on Cost-Efficient Feature Selection in Horizontal Federated Learning Background and Motivation As Federated Learning (FL) is increasingly recognized as a distributed machine learning paradigm that safeguards data privacy, its application to multi-client scenarios has garnered significant attention. In Horizontal Federated Learning (HFL), a...