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Can't use n_jobs argument in R package #180

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minor6th opened this issue Oct 30, 2020 · 1 comment
Open

Can't use n_jobs argument in R package #180

minor6th opened this issue Oct 30, 2020 · 1 comment
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enhancement New feature or request

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@minor6th
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minor6th commented Oct 30, 2020

I'm trying the R interpret package, the sample size is 100k with 100 features.
But I found that the training process is very slow and the function ebm_classify has no n_jobs argument.

@interpret-ml
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Hi @minor6th --

The R package is still very new and there's a lot more work we need to do in order to give it the same level of features as the more established python package. As you point out, training isn't parallelized currently in the R package, so it will be significantly slower on machines with many cores. Our plan is to move all the parallelism into the lower level C++ components where it can be shared across both python and R. We don't have a timeline yet for doing that work, but it will be at least several months. Once we have further news to share, we'll post it here in this issue.

-InterpretML team

@interpretml interpretml deleted a comment from rodrigovssp May 31, 2021
@paulbkoch paulbkoch added the enhancement New feature or request label Jan 24, 2023
@paulbkoch paulbkoch mentioned this issue Jan 24, 2023
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