In this post, I will summarize some dimension reduction methods.

  • PCA: Project x to z to maximize the variance
  • LDA: Projection maximize within-class scatter and minimize between class scatter
  • MDS: Projection keeping the orignial distances
  • Isomap: Use geodesic distance along the manifold instead of Euclidean distance
  • LLE: Linear patch assumption (linear combinations of neighbors)