Sparse discriminative feature selection

作者：

Highlights：

• The proposed method selects features that can preserve the sparse reconstructive relationship of the data.

• A greedy algorithm and a joint selection algorithm are devised to efficiently solve the proposed formulation.

• We incorporate discriminative analysis and l2;1_norm minimization into a joint feature selection.

摘要

Highlights•The proposed method selects features that can preserve the sparse reconstructive relationship of the data.•A greedy algorithm and a joint selection algorithm are devised to efficiently solve the proposed formulation.•We incorporate discriminative analysis and l2;1_norm minimization into a joint feature selection.

论文关键词：Joint feature selection,Sparse representation based classification,Discriminative learning

论文评审过程：Received 5 June 2014, Revised 16 September 2014, Accepted 16 October 2014, Available online 29 November 2014.

论文官网地址：https://doi.org/10.1016/j.patcog.2014.10.021