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 > >
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