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)