[scikit-learn] GradientBoostingRegressor, question about initialisation with MeanEstimator

Mathieu Blondel mathieu at mblondel.org
Sun Aug 28 00:30:05 EDT 2016


This comes from Algorithm 1, line 1, in "Greedy Function Approximation: a
Gradient Boosting Machine" by J. Friedman.

Intuitively, this has the same effect as fitting a bias (intercept) term in
a linear model. This allows the subsequent iterations (decision trees) to
work with centered targets.

Mathieu

On Wed, Aug 24, 2016 at 5:24 AM, Алексей Драль <aadral at gmail.com> wrote:

> Hi there,
>
> I recently found out that GradientBoostingRegressor uses MeanEstimator for
> the initial estimator in ensemble. Could you please point out (or
> explain) to the research showing superiority of this approach compared to
> the usage of DecisionTreeRegressor?
>
> --
> Yours sincerely,
> Alexey A. Dral
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn at python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20160828/13745653/attachment.html>


More information about the scikit-learn mailing list