Both SciPy and Numpy have built in functions for singular value decomposition (SVD). The commands are basically scipy.linalg.svd
and numpy.linalg.svd
. What is the difference between these two? Is any of them better than the other one?
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问题:
回答1:
Apart from the error checking, the actual work seems to be done within lapack
both with numpy
and scipy
.
Without having done any benchmarking, I guess the performance should be identical.