PCA_LDA_LPP_Tensor

所属分类:matlab编程
开发工具:matlab
文件大小:16KB
下载次数:778
上传日期:2007-04-09 16:18:23
上 传 者galaxyisland
说明:  PCA/LDA/LPP/TensorLPP/代码。 LPP是目前一种比较重要的子空间算法。基于Tensor的子空间算法,是传统PCA/LDA算法的进一步推广,具有重要意义。
(PCA/LDA/LO/TensorLPP/code. Alignment is a more important subspace algorithm. Based on the Tensor subspace algorithm, is a traditional PCA/LDA further promote algorithm is of great significance.)

文件列表:
PCA_LDA_LPP_Tensor (0, 2007-04-09)
PCA_LDA_LPP_Tensor\TensorLPP.m (5695, 2007-04-04)
PCA_LDA_LPP_Tensor\constructM.m (5339, 2007-04-04)
PCA_LDA_LPP_Tensor\constructW.m (10630, 2007-04-04)
PCA_LDA_LPP_Tensor\LDA.m (2239, 2007-04-04)
PCA_LDA_LPP_Tensor\LPP.m (5488, 2007-04-04)
PCA_LDA_LPP_Tensor\NPE.m (4731, 2007-04-04)
PCA_LDA_LPP_Tensor\OLPP.m (6620, 2007-04-04)
PCA_LDA_LPP_Tensor\PCA.m (6235, 2007-04-04)

Q & A: Q: How to use the code? A: You need to put LPP.m, PCA.m in your working directory. If you want to use constrctW to construct the affinity matrix, you should also put constructW.m in your working directory. 'help LPP' for detail information. 'help constructW' for details on how to construct the affinity matrix. Q: Why LPP code does not work in my application? A: If the number of samples is much larger than the number of features, you might need to use the Kernel LPP. The affinity graph construction plays a key role, you might need to constuct the affinity matrix by your own (based on your knowledge of your application). Please refer the following papers. Reference: Xiaofei He, and Partha Niyogi, "Locality Preserving Projections" Advances in Neural Information Processing Systems 16 (NIPS 2003), Vancouver, Canada, 2003. Xiaofei He, Shuicheng Yan, Yuxiao Hu, Partha Niyogi, and Hong-Jiang Zhang, "Face Recognition Using Laplacianfaces", IEEE PAMI, Vol. 27, No. 3, Mar. 2005. Deng Cai, Xiaofei He and Jiawei Han, "Document Clustering Using Locality Preserving Indexing" IEEE TKDE, 2005. Deng Cai, Xiaofei He and Jiawei Han, "Using Graph Model for Face Analysis", Technical Report, UIUCDCS-R-2005-2636, UIUC, Sept. 2005

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