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DOC add explanation of n_jobs in sklearn/model_selection/_validation.py #17717

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Jun 25, 2020
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DOC add explanation of n_jobs in sklearn/model_selection/_validation.py #17717

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889aea6
add explanation of n_jobs in _validation.py
hs-nazuna Jun 25, 2020
b99bd45
modify too long lines
hs-nazuna Jun 25, 2020
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19 changes: 13 additions & 6 deletions sklearn/model_selection/_validation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,7 +99,8 @@ def cross_validate(estimator, X, y=None, *, groups=None, scoring=None, cv=None,
``cv`` default value if None changed from 3-fold to 5-fold.

n_jobs : int, default=None
The number of CPUs to use to do the computation.
Number of jobs to run in parallel. Training the estimator and computing
the score are parallelized over the cross-validation splits.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
Expand Down Expand Up @@ -328,7 +329,8 @@ def cross_val_score(estimator, X, y=None, *, groups=None, scoring=None,
``cv`` default value if None changed from 3-fold to 5-fold.

n_jobs : int, default=None
The number of CPUs to use to do the computation.
Number of jobs to run in parallel. Training the estimator and computing
the score are parallelized over the cross-validation splits.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
Expand Down Expand Up @@ -703,7 +705,8 @@ def cross_val_predict(estimator, X, y=None, *, groups=None, cv=None,
``cv`` default value if None changed from 3-fold to 5-fold.

n_jobs : int, default=None
The number of CPUs to use to do the computation.
Number of jobs to run in parallel. Training the estimator and
predicting are parallelized over the cross-validation splits.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
Expand Down Expand Up @@ -1041,7 +1044,8 @@ def permutation_test_score(estimator, X, y, *, groups=None, cv=None,
Number of times to permute ``y``.

n_jobs : int, default=None
The number of CPUs to use to do the computation.
Number of jobs to run in parallel. Training the estimator and computing
the cross-validated score are parallelized over the permutations.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
Expand Down Expand Up @@ -1199,7 +1203,8 @@ def learning_curve(estimator, X, y, *, groups=None,
used to speed up fitting for different training set sizes.

n_jobs : int, default=None
Number of jobs to run in parallel.
Number of jobs to run in parallel. Training the estimator and computing
the score are parallelized over the different training and test sets.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
Expand Down Expand Up @@ -1474,7 +1479,9 @@ def validation_curve(estimator, X, y, *, param_name, param_range, groups=None,
``scorer(estimator, X, y)``.

n_jobs : int, default=None
Number of jobs to run in parallel.
Number of jobs to run in parallel. Training the estimator and computing
the score are parallelized over the combinations of each parameter
value and each cross-validation split.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
Expand Down