Learning correlation information for multi-label feature selection

Yuling Fan, Jinghua Liu, Jianeng Tang, Peizhong Liu, Yaojin Lin, Yongzhao Du

Abstract: Highlights•The proposed method is based on the embedding and filter approaches.•The label correlations are explored by an adaptive spectral graph.•The feature redundancy is analyzed by a general characteristic between features.•An efficient algorithm is designed to solve the optimization problem.