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)
good for visualization
dictionary learning
random trees embedding
independent component analysis