Other
Which covers almost all the data dimensionality reduction algorithm:
- Principal Component Analysis ('PCA')
- Linear Discriminant Analysis ('LDA')
- Independent Component Analysis ('ICA')
- Multidimensional scaling ('MDS')
- Isomap ('Isomap')
- Landmark Isomap ('LandmarkIsomap')
- Locally Linear Embedding ('LLE')
- Locally Linear Coordination ('LLC')
- Laplacian Eigenmaps ('Laplacian')
- Hessian LLE ('HessianLLE')
- Local Tangent Space Alignment ('LTSA')
- Diffusion maps ('DiffusionMaps')
- Kernel PCA ('KernelPCA')
- Generalized Discriminant Analysis ('KernelLDA')
- Stochastic Neighbor Embedding ('SNE')
- Neighborhood Preserving Embedding ('NPE')
- Linearity Preserving Projection ('LPP')
- Stochastic Proximity Embedding ('SPE')
- Linear Local Tangent Space Alignment ('LLTSA')
- Simple PCA ('SPCA')
- Conformal Eigenmaps ('CCA', im
matlab
工具箱
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