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Description: 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 techniques are available:
- Principal Component Analysis ( PCA )
- Linear Discriminant Analysis ( LDA )
- Multidimensional scaling ( MDS )
- Probabilistic PCA ( ProbPCA )
- Factor analysis ( FactorAnalysis )
- Sammon mapping ( Sammon )
- Isomap ( Isomap )
- Landmark Isomap ( LandmarkIsomap )
- Locally Linear Embedding ( LLE )
- Laplacian Eigenmaps ( Laplacian )
- Hessian LLE ( HessianLLE )
- Local Tangent Space Alignment ( LTSA )
- Diffusion maps ( DiffusionMaps )
- Kernel PCA ( KernelPCA )
- Generalized Discriminant Analysis ( KernelLDA )
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Author: yang |
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Author: Owen |
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Description: 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
Linear Discriminant Analysis (LDA)
Multidimensional scaling (MDS)
Isomap
Landmark Isomap
Local Linear Embedding (LLE)
Laplacian Eigenmaps
Hessian LLE
Local Tangent Space Alignment (LTSA)
Conformal Eigenmaps (extension of LLE)
Maximum Variance Unfolding (extension of LLE)
Landmark MVU (LandmarkMVU)
Fast Maximum Variance Unfolding (FastMVU)
Kernel PCA
Generalized Discriminant Analysis (GDA)
Diffusion maps
Stochastic Neighbor Embedding (SNE)
Symmetric SNE (SymSNE)
new: t-Distributed Stochastic Neighbor Embedding (t-SNE)
Neighborhood Preserving Embedding (NPE)
Locality Preserving Projection (LPP)
Linear Local Tangent Space Alignment (LLTSA)
Stochastic Proximity Embedding (SPE)
Mu
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Author: jdzsj |
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