[MRG] DOC n_jobs descriptions for forest.py
@@ -868,7 +868,9 @@ class RandomForestClassifier(ForestClassifier):
the generalization accuracy.
n_jobs : int or None, optional (default=None)
- The number of jobs to run in parallel for both `fit` and `predict`.
+ The number of jobs to run in parallel.
+ `fit`, `predict`, `decision_path` and `apply` are all
+ parallelized over the trees.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
@@ -1157,7 +1159,9 @@ class RandomForestRegressor(ForestRegressor):
the R^2 on unseen data.
n_jobs : int or None, optional (default=None)
- The number of jobs to run in parallel for both `fit` and `predict`.
+ The number of jobs to run in parallel.
+ `fit`, `predict`, `decision_path` and `apply` are all
+ parallelized over the trees.
`None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
@@ -1406,7 +1410,9 @@ class ExtraTreesClassifier(ForestClassifier):
the generalization accuracy.
n_jobs : int or None, optional (default=None)
- The number of jobs to run in parallel for both `fit` and `predict`.
+ The number of jobs to run in parallel.
+ `fit`, `predict`, `decision_path` and `apply` are all
+ parallelized over the trees.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
@@ -1671,7 +1677,9 @@ class ExtraTreesRegressor(ForestRegressor):
Whether to use out-of-bag samples to estimate the R^2 on unseen data.
n_jobs : int or None, optional (default=None)
- The number of jobs to run in parallel for both `fit` and `predict`.
+ The number of jobs to run in parallel.
+ `fit`, `predict`, `decision_path` and `apply` are all
+ parallelized over the trees.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
@@ -1874,7 +1882,9 @@ class RandomTreesEmbedding(BaseForest):
or to return a dense array compatible with dense pipeline operators.
n_jobs : int or None, optional (default=None)
- The number of jobs to run in parallel for both `fit` and `predict`.
+ The number of jobs to run in parallel.
+ `fit`, `transform`, `decision_path` and `apply` are all
+ parallelized over the trees.
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.
``-1`` means using all processors. See :term:`Glossary <n_jobs>`
for more details.
