Opening the book…
In linear algebra, the singular value decomposition (SVD) is a factorization of a real matrix into a rotation, followed by a rescaling followed by another rotation... Wikipedia: Singular value decomposition
Some properties:
When A is symetric U == V
When A is symetric U == EVector
If A is a Positive-definite matrix then S == EValue
Let us study the contribution of each singular value.
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