Hi Mathieu,
On Tue, Mar 8, 2016 at 6:45 PM, Mathieu Blondel
wrote:
> If this function is generally useful, it might be a good idea to make it
> public.
>
>
Agreed!
We're incorporating this in work we are doing to implement a method to
calculate confidence intervals for RandomForest predictions
If this function is generally useful, it might be a good idea to make it
public.
Mathieu
On Wed, Mar 9, 2016 at 1:29 AM, Ariel Rokem wrote:
>
> On Mon, Mar 7, 2016 at 8:24 AM, Andreas Mueller wrote:
>
>> Hi Ariel.
>> We are not storing them any more because of memory issues, but you can
>> rec
On Mon, Mar 7, 2016 at 8:24 AM, Andreas Mueller wrote:
> Hi Ariel.
> We are not storing them any more because of memory issues, but you can
> recover them using the random state of the tree:
>
> https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/forest.py#L76
>
> > indices
Hi Ariel.
We are not storing them any more because of memory issues, but you can
recover them using the random state of the tree:
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/forest.py#L76
> indices = _generate_sample_indices(tree.random_state, n_samples)
Hth,
Andy
Hi everyone,
Is there some way to identify the samples that were used in constructing
each tree in a RandomForest* object?
I am looking for the equivalent of "keep.inbag" in this R implementation:
http://math.furman.edu/~dcs/courses/math47/R/library/randomForest/html/randomForest.html
Thanks!
A
