AI engineering glossary · Linear algebra
What is whitening transformation?
Whitening transformation (also called Sphering): A linear transformation applied to data so that its features become uncorrelated and have unit variance, making its covariance matrix the identity. It is usually computed from the eigendecomposition of the covariance matrix.
Whitening transformation: an example
After whitening, a 2-feature dataset stretched along a diagonal becomes a round cloud whose covariance matrix is [[1,0],[0,1]].
Related terms
More Linear algebra terms
- Affine transformation
- Augmented matrix
- Basis
- Batch matrix multiplication
- Change of basis
- Characteristic polynomial
- Cholesky decomposition
- Column space
Where you learn it
Whitening transformation is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.