Dear all, I tried using the 'scipy.sparse.eigs' tool for performing principal component analysis on a matrix which is roughly 80% sparse.
First of all, is that a good way to go about it? Second, the operation failed when the function failed to converge on accurate eigenvalues. I noticed the 'tol' attribute in the function, but how does one define a reasonable tolerance and calculate it? Thanks
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