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

[Алексей Драль]

Hi Mathieu,

I was looking exactly for this article. Thank you very much.

2016-08-28 5:30 GMT+01:00 Mathieu Blondel <mathieu at mblondel.org>:

> 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
>>
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>>
>
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-- 
Yours sincerely,
Alexey A. Dral
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