Dimensionality Reduction#

Linear Projection#

  • principal component analysis (PCA)

  • singular value decomposition

  • random projection

Manifold Learning#

This is also knon as nonlinear dimensionality reduction.

  • isomap

  • multidimensional scaling (MDS) - good for visualization

  • locally linear embedding (LLE)

  • t-distributed stochastic neighbor embedding (t-SNE)

  • dictionary learning

  • random trees embedding

  • independent component analysis