Hi Mathieu, I was looking exactly for this article. Thank you very much.
2016-08-28 5:30 GMT+01:00 Mathieu Blondel <[email protected]>: > 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 <[email protected]> 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 >> [email protected] >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > > -- Yours sincerely, Alexey A. Dral
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