Drop in replacement for sklearn.model_selection.permutation_test_score
It'd be great to have a dask wrapper for permutation_test_score so that permutations of gridsearches are easier to run in dask.
Hi Dask-ml folks, just bumping this up. Is there anyone with interest/expertise who could look into this?
I think it'd be possible to use Dask-ML's joblib backend because the implementation of permutation_test_score relies on joblib: github.com/scikit-learn/scikit-learn/.../sklearn/model_selection/_validation.py#L1308
I was hoping to run the permutations across a cluster that uses slurm.
From the docs of Dask-ML's joblib backend:
Dask can scale these Joblib-backed algorithms out to a cluster of machines by providing an alternative Joblib backend. The following video demonstrates how to use Dask to parallelize a grid search across a cluster.
The video indicates that joblib will use Dask-ML's computational resources instead of the local machines computational resources, which should work near seamlessly with the SLURM backend. Are you observing something different?