Introduction - If you have any usage issues, please Google them yourself
,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 )