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MATLAB_Codes_for_Dimensionality_Reduction
- 数据降维工具箱，包括一些典型算法，例如pca，lle，mds，lda等。
mani
- 包含了大多数流形学习方法的代码,有PCA,ISOMAP,LLE,HLLE
Dimension-reduction--toolbox
- 该工具箱中包含了多种降维算法。其中有传统的PCA和Local PCA算法，也有典型的流形学习算法，如Isomap、LLE、HLLE、Laplacian Eigenmaps 和 Local Tangent Space 。-The toolbox contains a variety of dimensionality reduction algorithms. In which the traditional PCA and Local PCA algorithms, there are the
pca_lle_matlab
- 国外模式识别课上老师给的pca和lle代码-These codes are given by the teacher in the pattern recognition class
lle_and_pca
- 实现lle和pca的matlab编程，主要目的是比较lle和pca这两个高维数据降维方法的性能，各有所长。-Use matlab to realise lle and pca ，the purpose is to compare lle and pca，which reduce high dimension data to low data dimension，and each has advantage！
mani
- 流形学习的经典算法，包括有:PCA,MDS,ISOMAP,LLE,Hessian LLE,LTSA, Laplacian,Diffusion Map-The classic manifold learning algorithm, including: PCA, MDS, ISOMAP, LLE, Hessian LLE, LTSA, Laplacian, Diffusion Map
drtoolbox
- Matlab针对各种数据预处理的降维方法，源码集合。-Currently, the Matlab Toolbox for Dimensionality Reduction contains the following techniques: Principal Component Analysis (PCA) Probabilistic PCA Factor Analysis (FA) Sammon mapping Lin
Blob-Code
- 多种模式识别算法的介绍，包括PCA，MPCA，LLE等-Several pattern recognition algorithm is introduced, including PCA, MPCA, LLE etc.
techniques
- 这是一个非常有用的程序主要是用来光谱降维处理的手段有PCA,LCA,LLE,Isomap等-This is a very useful procedure mainly used for spectral dimension reduction processing by means of PCA, LCA, LLE, Isomap, etc.
MATLAB Codes for Dimensionality Reduction
- 子空间学习方法工具箱，包含PCA、LDA、LLE、ISOMAP等经典子空间分析方法(Subspace learning method toolbox, including classical subspace analysis methods such as PCA, LDA, LLE, ISOMAP and so on)
mani
- 流形学习主要方法的可视化界面，包括LLE、ISOMAP、LE、PCA等方法和8种经典测试流形数据。(Visulization interface for mainfold learning methods)
Matlab Toolbox for Dimensionality Reduction.tar
- matlab 常用的降维软件 包括常用LLE、PCA、CCA等算法，简单好用