Thanks, Jeff, that was what I expected, but I just wanted to make sure. I will
add a note via a pull request later.
> On Jul 6, 2015, at 3:52 PM, Jeff Blackburne <jblackbu...@gmail.com> wrote:
>
> Hi Sebastian,
>
> The bootstrap sample size is always the same as the input sample size. If you
> feel up to it, a pull request updating the documentation would probably be
> quite welcome.
>
> -Jeff
>
>
> On Mon, Jul 6, 2015 at 12:21 PM, Sebastian Raschka <se.rasc...@gmail.com
> <mailto:se.rasc...@gmail.com>> wrote:
> Hi, all,
>
> I am wondering what the sample size of the bootstrap samples are in the
> RandomForestClassifier/Regressor (if bootstrap=True, default setting). From
> the documentation
>
> http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier
>
> <http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier>:
> > [...] that fits a number of decision tree classifiers on various
> > sub-samples of the dataset
>
> and
>
> http://scikit-learn.org/stable/modules/ensemble.html#random-forests
> <http://scikit-learn.org/stable/modules/ensemble.html#random-forests>:
> > [...] each tree in the ensemble is built from a sample drawn with
> > replacement (i.e., a bootstrap sample) from the training set.
>
> Is the sample size of the bootstrap sample equal to the "original" sample
> size in the training set? If not, can it be controlled somehow? Maybe a short
> note could be added to the documentation for clarity.
>
> Best,
> Sebastian
>
>
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