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mkolod/dense_to_sparse_csr.ipynb

Last active August 28, 2019 17:03
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mkolod commented Aug 28, 2019

We can see that for a matrix that's only 75% sparse, CSR saves hardly any memory, and is more costly computationally. Typically, matrices have to be over 99% sparse (preferably 99.9%) for a sparse representation to be more computationally performant. The requirement for substantial memory savings are a bit less stringent, but 99%+ sparsity is a good general rule of thumb.

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