Explain why you would choose to use Singular Value Decomposition (SVD) instead of PCA in this specific application. Justify your choice and discuss any tradeoffs involved.

We would choose SVD over PCA because SVD can decompose all matrices, regardless of their properties. This is particularly useful when dealing with numerical instability or matrices that cannot be decomposed into eigenvalues and eigenvectors. However, this comes at the cost of increased computational complexity and memory usage.