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Population theory for boosting ensembles. (English) Zbl 1105.62308
Summary: Tree ensembles are looked at in distribution space, that is, the limit case of “infinite” sample size. It is shown that the simplest kind of trees is complete in \(D\)-dimensional \(L_2(P)\) space if the number of terminal nodes \(T\) is greater than \(D\). For such trees we show that the AdaBoost algorithm gives an ensemble converging to the Bayes risk.

MSC:
62F15 Bayesian inference
62H30 Classification and discrimination; cluster analysis (statistical aspects)
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