Research on Feature Selection Methods Based on Hypergraph Theory in Multi-scale Decision Information System

Feature selection is critical for enhancing data processing efficiency and decision accuracy. In multi-scale decision information systems, a novel hypergraph-based feature selection method is proposed to address the challenge of selecting the optimal scale combination from multi-scale features. An adjacency relationship matrix is defined to induce a hypergraph, which visualizes the relationships among multi-scale features and transforms the feature selection problem into a minimal vertex cover problem within the hypergraph. This approach facilitates the selection of the optimal scale feature subset. Additionally, the algorithm incorporates a priority queue to manage the sorting of features, significantly reducing time complexity and improving solution efficiency.