Abstract: Feature selection (FS) is crucial for dimensionality reduction. However, existing methods struggle with high-dimensional feature redundancy and complex associations. These limitations hinder ...

Abstract: Gene expression data usually present the characteristics of high dimension and small sample size. In such data, it is crucial to conduct feature selection to reduce dimensions and retain key ...