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Face Recognition Using Kernel Direct Discriminant Analysis Algorithms
and Matlab source codes for the kernel direct discriminant analysis (KDDA) -Face Recognition Using Kernel Direct Disc riminant Analysis Algorithms and Matlab sourc e codes for th
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这是一个MATLAB工具箱包括32个降维程序，主要包括 pca,lda,MDS等十几个程序包，对于图像处理非常具有参考价值- ，This Matlab toolbox implements 32 techniques for dimensionality reduction. These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. The following techn
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基于局部Fisher准则的非线性核Fisher辨别分析，应用于有监督的特征提取与高维数据的有效降维。-Kernel Local Fisher Discriminant Analysis for Supervised Dimensionality Reduction.
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不仅使用了kernel trick ，还是用了加权的最大边缘规则，获得较好的识别效果。-A new kernel-based learning algorithm, called kernel weighted maximum margin
discriminant analysis (KWMMDA), is presented in this paper. Different from the previous
discriminant analysis algorithms base
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学姐做地理学研究时用的核Fisher判别分析的代码-Sister doing geography research time by the kernel Fisher discriminant analysis codes
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