Chao Chen

Multi-Label Causal Feature Selection Based on Unary Approximate Markov Blankets

Multi-label feature selection (FS) plays a vital role in multi-label learning as properly selected features can be used to substantively improve classification performance and reduce training time of a classifier. Existing multi-label FS methods primarily rely on the correlations among variables but neglect causality,...