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

                                            

 

 

Transformation using SVD
  • Transformed data
  • is called SVD transform matrix
  • Essentially, is just a rotation of
  • Dimensionality of is
  • different basis vectors than the original space
  • Columns of give the basis vectors in rotated space
  • shows how each dimension can be represented as a linear combination of other dimensions
 
  • Columns are input basis vectors
  • shows how each object can be represented as a linear combination of other objects
 
  • Columns are output basis vectors
  • Lengths of vectors are preserved