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Basically, at what sparsity level does having sparse data improve things.
e.i. should a dataset with 10% be converted to a dcgmatrix or stay a matrix?
there are kinda two scenarios. you have sparse tibbles, or dense tibble with a lot of zeroes
The text was updated successfully, but these errors were encountered:
This was done in https://github.com/tidymodels/benchmark-sparsity-threshold.
We will use the results of the analysis in tidymodels/workflows#271
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Basically, at what sparsity level does having sparse data improve things.
e.i. should a dataset with 10% be converted to a dcgmatrix or stay a matrix?
there are kinda two scenarios. you have sparse tibbles, or dense tibble with a lot of zeroes
The text was updated successfully, but these errors were encountered: