Causal forest are a very nice work. However, they deal with causal
inference, rather than prediction. Hence, I am not really sure how we
could implement them in the API of scikit-learn. Do you have a
suggestion?
Cheers,
Gaël
On Fri, May 24, 2019 at 05:21:50PM -0400, Randy Ellis wrote:
> Would t
We've released 0.21.2 primarily to fix an issue with euclidean_distances
(and pairwise_distances). It should be available on PyPI and Conda-Forge.
Full list of changes at https://scikit-learn.org/0.21/whats_new/v0.21.html
Thanks to all who helped fix these issues so quickly after 0.21.1.
Sorry, didn't see this one already went through! Whoops.
On Fri, 24 May 2019 at 17:41, Olivier Grisel
wrote:
> A quick bugfix release to fix a critical regression in the computation
> of the euclidean distances returning incorrect values silently.
>
> This release also includes other bugfixes li
For some of the larger PRs, this might be helpful. Not going to help where
the intricacies of Scikit-learn API come in play.
On Sat, 25 May 2019 at 04:17, Andreas Mueller wrote:
> Hi All.
> What do you think of https://www.pullrequest.com/googleserve/?
> It's sponsored code reviews. Could be int
