Hi,
There is a very advanced pull request which add sparse matrix support to
decision tree: https://github.com/scikit-learn/scikit-learn/pull/3173
Based on this, it could be possible to have gradient tree boosting working
on sparse data. Note that adaboost already support sparse matrix
with non-tree based estimator.
Best regards,
Arnaud
On 16 Sep 2014, at 02:16, c TAKES <ctakesli...@gmail.com> wrote:
> Is anyone working on making Gradient Boosting Regressor work with sparse
> matrices?
>
> Or is anyone working on adding an option for fully corrective gradient
> boosting, I.E. all trees in the ensemble are re-weighted at each iteration?
>
> These are things I would like to see and may be able to help with if no one
> is currently working on them.
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