关键词: 成对约束，稀疏保持，半监督降维

Abstract: A kind of algorithm called Pairwise Constraint Projections inosculating Sparsity Preserving (SPPCP) was proposed,which introduces Sparsity Preserving Projections(SPP) with trade-off parameter in the process of pairwise constraint-guided dimensional reduction,preserving pairwise constraint feature and heriting the special character of geo- metrical structure preserving and neighbor preserving from sparsity preserving. Experiments operated on UCI databases and AR face database show that the algorithm inosculates merits of SPP effectively. Compared with the typical semi su- pervised dimensional reduction algorithms based on pairwise constraint, the algorithm can improve the accuracy and sta- bility of classified algorithms based on the shortest Euclidean distance.

Key words: Pairwise constraints, Sparsity preserving, Semi-supervised dimensional reduction