0 摘要

In this paper, another strategy to learn from multi-label data is studied, where label-specific features are exploited to benefit the discrimination of different class labels.
Accordingly, an intuitive yet effective algorithm named LIFT, i.e. multi-label learning with Label specIfic FeaTures, is proposed.