广义的监督局部保留投影算法

王晓明; 王士同

doi:10.3724/SP.J.1146.2008.00946

广义的监督局部保留投影算法

doi: 10.3724/SP.J.1146.2008.00946

基金项目:

国家863计划项目(2007AA1Z158，2006AA10Z313)和国家自然科学基金(60704047)资助课题

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出版历程
- 收稿日期: 2008-07-24
- 修回日期: 2009-03-09
- 刊出日期: 2009-08-19

Generalized Supervised Locality Preserving Projection

摘要

摘要: 针对监督的局部保留投影算法(Supervised Locality Preserving Projection，SLPP)在小样本情况下矩阵的奇异性问题，该文提出了一种广义的监督局部保留投影算法(Generalized Supervised Locality Preserving Projection，GSLPP)。GSLPP在大样本情况下等价于SLPP，在小样本情况下却可以等价转换到一个低维空间中来求解，从而有效解决了小样本问题。最后，实验结果验证了该方法的有效性。
- 特征提取;局部保留投影;监督局部保留投影
Abstract: Supervised Locality Preserving Projection (SLPP) is a generalization of Locality Preserving Projection (LPP) in the case of supervised learning. In this paper the drawback of SLPP in the high-dimensional and small sample size case is pointed out, and a new algorithm called Generalized Supervised Locality Preserving Projection (GSLPP) is proposed. The relationship between SLPP and GSLPP is theoretically analyzed. In the small sample size case GSLPP can be solved equivalently in lower-dimensionality space. Finally, the effectiveness of the proposed algorithm is verified by experimental results.

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