Singular value decomposition

Also: SVD

Factoring any matrix into a rotation, a scaling and another rotation, with the scale factors ordered by size. Keeping only the largest gives the best possible low-rank approximation, which is what PCA and low-rank adaptation both rest on.

A definition is not an understanding. This is taught properly in Norms, projections and decompositions, part of Linear algebra.

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Terms from the same topic

PCA Vector Matrix Dot product Matrix multiplication Eigenvector