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一种新的基于MMC和LSE的监督流形学习算法

DOI: 10.3724/SP.J.1004.2013.02077, PP. 2077-2089

Keywords: 局部样条嵌入,最大边缘准则,特征提取,流形学习

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Abstract:

?针对局部样条嵌入算法(Localsplineembedding,LSE)存在样本外点学习和无监督模式学习问题,本文提出了一种新颖的正交局部样条判别投影算法(O-LSDP).该算法通过引入明确的线性映射关系,构建平移缩放模型,以及正交化特征子空间,从而使该算法能够应用于模式分类问题并显著改善了算法的分类识别能力.在标准人脸数据库和植物叶片数据库上的实验结果验证了该算法的有效性与可行性.

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