Module 6: Dimensionality Reduction
  Lecture 29: Singular Value Decomposition (SVD)
 

                                            

 

 

Dimensionality reduction using SVD
  • Use only dimensions
  • Retain first columns for and and first values for
  • First columns of give the basis vectors in reduced space
  • Best rank approximation in terms of sum squared error