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DOC add explanation of n_jobs in permutation_importance #17723

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Jun 25, 2020
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DOC add explanation of n_jobs in permutation_importance #17723

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3 changes: 2 additions & 1 deletion sklearn/inspection/_permutation_importance.py
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Expand Up @@ -75,7 +75,8 @@ def permutation_importance(estimator, X, y, *, scoring=None, n_repeats=5,
Number of times to permute a feature.

n_jobs : int or None, default=None
The number of jobs to use for the computation.
Number of jobs to run in parallel. The computation is done by computing
permutation score for each columns and parallelized over the columns.
`None` means 1 unless in a :obj:`joblib.parallel_backend` context.
`-1` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
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