ARISE: An adaptive residual-informed stability ensemble for feature selection in small-sample biomedical omics
ARISE is a novel feature selection method for small-sample molecular data, designed to find predictive and stable feature subsets. It combines seven relevance signals with class-balanced stability assessment and redundancy control to manage relevance, stability, redundancy, and multiclass discrimination simultaneously. The method consistently outperformed other approaches across various datasets and classifiers.