A multi-label classification algorithm based on label-specific features
Huaqiao Qu, Shichao Zhang, Huawen Liu, Jianmin Zhao · Wuhan University Journal of Natural Sciences · 2011
Aiming at the problem of multi-label classification, a multi-label classification algorithm based on label-specific features is proposed in this paper. In this algorithm, we compute feature density on the positive and negative instances set of each class firstly and then select m k features of high density from the positive and negative instances set of each class, respectively; the intersection is taken as the label-specific features of the corresponding class. Finally, multi-label data are classified on the basis of label-specific features. The algorithm can show the label-specific features of each class. Experiments show that our proposed method, the MLSF algorithm, performs significantly better than the other state-of-the-art multi-label learning approaches.