Hi Mathieu,
On Tue, Mar 8, 2016 at 6:45 PM, Mathieu Blondel <math...@mblondel.org>
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 (based on this
previous work in R: https://github.com/swager/randomForestCI). We've
started some preliminary work in a github repo of our own (
https://github.com/arokem/erlking), but we would be happy to contribute any
of this into the sklearn eco-system, if that's a good thing.
Cheers,
Ariel
> Mathieu
>
> On Wed, Mar 9, 2016 at 1:29 AM, Ariel Rokem <aro...@gmail.com> wrote:
>
>>
>> On Mon, Mar 7, 2016 at 8:24 AM, Andreas Mueller <t3k...@gmail.com> 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 = _generate_sample_indices(tree.random_state, n_samples)
>>>
>>>
>> Yes - very helpful - thanks! I have recorded our full solution for
>> posterity (and for google-ability) here:
>> http://stackoverflow.com/questions/35832786/in-bag-for-randomforest-objects/35872711
>>
>>
>>
>>> Hth,
>>> Andy
>>>
>>>
>>>
>>> On 03/04/2016 07:04 PM, Ariel Rokem wrote:
>>>
>>> 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!
>>>
>>> Ariel
>>>
>>>
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