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)