DOC Update docstring of RFs regarding max_samples
@@ -884,9 +884,9 @@ class RandomForestClassifier(ForestClassifier):
A random forest is a meta estimator that fits a number of decision tree
classifiers on various sub-samples of the dataset and uses averaging to
improve the predictive accuracy and control over-fitting.
- The sub-sample size is always the same as the original
- input sample size but the samples are drawn with replacement if
- `bootstrap=True` (default).
+ The sub-sample size is controlled with the `max_samples` parameter if
+ `bootstrap=True` (default), otherwise the whole dataset is used to build
+ each tree.
Read more in the :ref:`User Guide <forest>`.
@@ -1202,9 +1202,9 @@ class RandomForestRegressor(ForestRegressor):
A random forest is a meta estimator that fits a number of classifying
decision trees on various sub-samples of the dataset and uses averaging
to improve the predictive accuracy and control over-fitting.
- The sub-sample size is always the same as the original
- input sample size but the samples are drawn with replacement if
- `bootstrap=True` (default).
+ The sub-sample size is controlled with the `max_samples` parameter if
+ `bootstrap=True` (default), otherwise the whole dataset is used to build
+ each tree.
Read more in the :ref:`User Guide <forest>`.
