[scikit-learn] time complexity of tree-based model?

I do some benchmark in my experiments and I almost use ensemble-based regressor. What is the time complexity if I use random forest regressor? Assume I only set variable * estimators=100* and others doesn't enter. thx ___ scikit-learn mailing list sciki

Re: [scikit-learn] Next Sprint

I would propose the week of Feb 25th, as I heard people say that they might be available at this time. It is good for many people, or should we organize a doodle? G On Wed, Dec 19, 2018 at 05:27:21PM -0500, Andreas Mueller wrote: > Can we please nail down dates for a sprint? > On 11/20/18 2:25

Re: [scikit-learn] benchmarking TargetEncoder Was: ANN Dirty_cat: learning on dirty categories

On 12/15/18 7:35 AM, Joris Van den Bossche wrote: Op vr 14 dec. 2018 om 16:46 schreef Andreas Mueller >: As far as I understand, the open PR is not a leave-one-out TargetEncoder? I would want it to be :-/ I also did not yet add the CountFeaturizer fr

Re: [scikit-learn] Next Sprint

Can we please nail down dates for a sprint? On 11/20/18 2:25 PM, Gael Varoquaux wrote: On Tue, Nov 20, 2018 at 08:15:07PM +0100, Olivier Grisel wrote: We can also do Paris in April / May or June if that's ok with Joel and better for Andreas. Absolutely. My thoughts here are that I want to min