SVD dimensions #8418
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jakevdp
EngineerKhan
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SVD dimensions
#8418
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Asking it out of curiosity. If I apply SVD as: Why does it give |
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Answered by
jakevdp
Nov 1, 2021
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I suspect the reason for this is primarily memory savings: if you're doing a large SVD, it's wasteful to return a large matrix that is by definition mostly zeros, when (1) many applications need just the singular values, and (2) it's straightforward to construct the full matrix if needed. |
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bis returned as a one-dimensional array of singular values, following the standard convention used by NumPy and other numerical computing packages.I suspect the reason for this is primarily memory savings: if you're doing a large SVD, it's wasteful to return a large matrix that is by definition mostly zeros, when (1) many applications need just the singular values, and (2) it's straightforward to construct the full matrix if needed.